High-Throughput doi: 10.3390/ht9030017

Authors: Eric Banan-Mwine Daliri Fred Kwame Ofosu Ramachandran Chelliah Byong Hoon Lee Deog-Hwan Oh

Recent advances in microbiome studies have revealed much information about how the gut virome, mycobiome, and gut bacteria influence health and disease. Over the years, many studies have reported associations between the gut microflora under different pathological conditions. However, information about the role of gut metabolites and the mechanisms by which the gut microbiota affect health and disease does not provide enough evidence. Recent advances in next-generation sequencing and metabolomics coupled with large, randomized clinical trials are helping scientists to understand whether gut dysbiosis precedes pathology or gut dysbiosis is secondary to pathology. In this review, we discuss our current knowledge on the impact of gut bacteria, virome, and mycobiome interactions with the host and how they could be manipulated to promote health.

High-Throughput doi: 10.3390/ht9030016

Authors: Malena Serrano Eric Climent Fernando Freire Juan F. Martínez-Blanch Carmen González Luis Reyes M. Carmen Solaz-Fuster Jorge H. Calvo M. Ángeles Jiménez Francisco M. Codoñer

To date, there is a lack of research into the vaginal and sperm microbiome and its bearing on artificial insemination (AI) success in the ovine species. Using hypervariable regions V3–V4 of the 16S rRNA, we describe, for the first time, the combined effect of the ovine microbiome of both females (50 ewes belonging to five herds) and males (five AI rams from an AI center) on AI outcome. Differences in microbiota abundance between pregnant and non-pregnant ewes and between ewes carrying progesterone-releasing intravaginal devices (PRID) with or without antibiotic were tested at different taxonomic levels. The antibiotic treatment applied with the PRID only altered Streptobacillus genus abundance, which was significantly lower in ewes carrying PRID with antibiotic. Mageebacillus, Histophilus, Actinobacilllus and Sneathia genera were significantly less abundant in pregnant ewes. In addition, these genera were more abundant in two farms with higher AI failure. Species of these genera such as Actinobacillus seminis and Histophilus somni have been associated with reproductive disorders in the ovine species. These genera were not present in the sperm samples of AI rams, but were found in the foreskin samples of rams belonging to herd 2 (with high AI failure rate) indicating that their presence in ewes’ vagina could be due to prior transmission by natural mating with rams reared in the herd.

High-Throughput doi: 10.3390/ht9030015

Authors: Nelson Perdigão Pedro M. C. Pina Cátia Rocha João Manuel R. S. Tavares Agostinho Rosa

There is a misconception that intrinsic disorder in proteins is equivalent to darkness. The present study aims to establish, in the scope of the Swiss-Prot and Dark Proteome databases, the relationship between disorder and darkness. Three distinct predictors were used to calculate the disorder of Swiss-Prot proteins. The analysis of the results obtained with the used predictors and visualization paradigms resulted in the same conclusion that was reached before: disorder is mostly unrelated to darkness.

High-Throughput doi: 10.3390/ht9020014

Authors: Omar Rossi Eleonora Molesti Allan Saul Carlo Giannelli Francesca Micoli Francesca Necchi

Despite the huge decrease in deaths caused by Shigella worldwide in recent decades, shigellosis still causes over 200,000 deaths every year. No vaccine is currently available, and the morbidity of the disease coupled with the rise of antimicrobial resistance renders the introduction of an effective vaccine extremely urgent. Although a clear immune correlate of protection against shigellosis has not yet been established, the demonstration of the bactericidal activity of antibodies induced upon vaccination may provide one means of the functionality of antibodies induced in protecting against Shigella. The method of choice to evaluate the complement-mediated functional activity of vaccine-induced antibodies is the Serum Bactericidal Assay (SBA). Here we present the development and intra-laboratory characterization of a high-throughput luminescence-based SBA (L-SBA) method, based on the detection of ATP as a proxy of surviving bacteria, to evaluate the complement-mediated killing of human sera. We demonstrated the high specificity of the assay against a homologous strain without any heterologous aspecificity detected against species-related and non-species-related strains. We assessed the linearity, repeatability and reproducibility of L-SBA on human sera. This work will guide the bactericidal activity assessment of clinical sera raised against S. sonnei. The method has the potential of being applicable with similar performances to determine the bactericidal activity of any non-clinical and clinical sera that rely on complement-mediated killing.

High-Throughput doi: 10.3390/ht9020013

Authors: Claudia Strafella Valerio Caputo Giulia Campoli Rosaria Maria Galota Julia Mela Stefania Zampatti Giulietta Minozzi Cristina Sancricca Serenella Servidei Emiliano Giardina Raffaella Cascella

Genetic counseling applied to limb–girdle muscular dystrophies (LGMDs) can be very challenging due to their clinical and genetic heterogeneity and the availability of different molecular assays. Genetic counseling should therefore be addressed to select the most suitable approach to increase the diagnostic rate and provide an accurate estimation of recurrence risk. This is particularly true for families with a positive history for recessive LGMD, in which the presence of a known pathogenetic mutation segregating within the family may not be enough to exclude the risk of having affected children without exploring the genetic background of phenotypically unaffected partners. In this work, we presented a family with a positive history for LGMD2A (OMIM #253600, also known as calpainopathy) characterized by compound heterozygosity for two CAPN3 mutations. The genetic specialist suggested the segregation analysis of both mutations within the family as a first-level analysis. Sequentially, next-generation sequencing (NGS) analysis was performed in the partners of healthy carriers to provide an accurate recurrence/reproductive risk estimation considering the genetic background of the couple. Finally, this work highlighted the importance of providing a genetic counseling/testing service even in unaffected individuals with a carrier partner. This approach can support genetic counselors in estimating the reproductive/recurrence risk and eventually, suggesting prenatal testing, early diagnosis or other medical surveillance strategies.

High-Throughput doi: 10.3390/ht9020012

Authors: Rossella Tomaiuolo Iolanda Veneruso Federica Cariati Valeria D’Argenio

During the last decade, the availability of next-generation sequencing-based approaches has revealed the presence of microbial communities in almost all the human body, including the reproductive tract. As for other body sites, this resident microbiota has been involved in the maintenance of a healthy status. As a consequence, alterations due to internal or external factors may lead to microbial dysbiosis and to the development of pathologies. Female reproductive microbiota has also been suggested to affect infertility, and it may play a key role in the success of assisted reproductive technologies, such as embryo implantation and pregnancy care. While the vaginal microbiota is well described, the uterine microbiota is underexplored. This could be due to technical issues, as the uterus is a low biomass environment. Here, we review the state of the art regarding the role of the female reproductive system microbiota in women’s health and human reproduction, highlighting its contribution to infertility.

High-Throughput doi: 10.3390/ht9020011

Authors: Konstantin O. Butenko Inna A. Chaban Eugene V. Skurat Olga A. Kondakova Yuri F. Drygin

A genetically engineered chimeric virus crTMV-CP-PLRV composed of the crucifer-infecting tobacco mosaic virus (crTMV) RNA and the potato leafroll virus (PLRV) coat protein (CP) was obtained by agroinfiltration of Nicotiana benthamiana with the binary vector pCambia-crTMV-CPPLRV. The significant levels of the chimeric virus enabled direct visualization of crTMV-CP-PLRV in the cell and to investigate the mechanism of the pathogenesis. Localization of the crTMV-CP-PLRV in plant cells was examined by immunoblot techniques, as well as light, and transmission electron microscopy. The chimera can transfer between vascular and nonvascular tissues. The chimeric virus inoculum is capable to infect N. benthamiana mechanically. The distinguishing feature of the chimeric virus, the RNA virus with the positive genome, was found to localize in the nucleolus. We also investigated the role of the N-terminal sequence of the PLRV P3 coat protein in the cellular localization of the virus. We believe that the gene of the PLRV CP can be substituted with genes from other challenging-to-study plant pathogens to produce other useful recombinant viruses.

High-Throughput doi: 10.3390/ht9020010

Authors: Rossella Tomaiuolo Iolanda Veneruso Federica Cariati Valeria D’Argenio

The increasing interest in metagenomics is enhancing our knowledge regarding the composition and role of the microbiota in human physiology and pathology. Indeed, microbes have been reported to play a role in several diseases, including infertility. In particular, the male seminal microbiota has been suggested as an important factor able to influence couple’s health and pregnancy outcomes, as well as offspring health. Nevertheless, few studies have been carried out to date to deeper investigate semen microbiome origins and functions, and its correlations with the partner’s reproductive tract microbiome. Here, we report the state of the art regarding the male reproductive system microbiome and its alterations in infertility.

High-Throughput doi: 10.3390/ht9020009

Authors: Rúben Araújo Luís Ramalhete Helder Da Paz Edna Ribeiro Cecília R.C. Calado

Epigallocatechin-3-gallate (EGCG), the major catechin present in green tea, presents diverse appealing biological activities, such as antioxidative, anti-inflammatory, antimicrobial, and antiviral activities, among others. The present work evaluated the impact in the molecular profile of human plasma from daily consumption of 225 mg of EGCG for 90 days. Plasma from peripheral blood was collected from 30 healthy human volunteers and analyzed by high-throughput Fourier transform infrared spectroscopy. To capture the biochemical information while minimizing the interference of physical phenomena, several combinations of spectra pre-processing methods were evaluated by principal component analysis. The pre-processing method that led to the best class separation, that is, between the plasma spectral data collected at the beginning and after the 90 days, was a combination of atmospheric correction with a second derivative spectra. A hierarchical cluster analysis of second derivative spectra also highlighted the fact that plasma acquired before EGCG consumption presented a distinct molecular profile after the 90 days of EGCG consumption. It was also possible by partial least squares regression discriminant analysis to correctly predict all unlabeled plasma samples (not used for model construction) at both timeframes. We observed that the similarity in composition among the plasma samples was higher in samples collected after EGCG consumption when compared with the samples taken prior to EGCG consumption. Diverse negative peaks of the normalized second derivative spectra, associated with lipid and protein regions, were significantly affected (p < 0.001) by EGCG consumption, according to the impact of EGCG consumption on the patients’ blood, low density and high density lipoproteins ratio. In conclusion, a single bolus dose of 225 mg of EGCG, ingested throughout a period of 90 days, drastically affected plasma molecular composition in all participants, which raises awareness regarding prolonged human exposure to EGCG. Because the analysis was conducted in a high-throughput, label-free, and economic analysis, it could be applied to high-dimension molecular epidemiological studies to further promote the understanding of the effect of bio-compound consumption mode and frequency.

High-Throughput doi: 10.3390/ht9020008

Authors: Giuseppe Agapito Marzia Settino Francesca Scionti Emanuela Altomare Pietro Hiram Guzzi Pierfrancesco Tassone Pierosandro Tagliaferri Mario Cannataro Mariamena Arbitrio Maria Teresa Di Martino

The knowledge of genetic variants in genes involved in drug metabolism may be translated into reduction of adverse drug reactions, increase of efficacy, healthcare outcomes improvement and economic benefits. Many high-throughput tools are available for the genotyping of Single Nucleotide Polymorphisms (SNPs) known to be related to drugs and xenobiotics metabolism. DMETTM platform represents an example of SNPs panel to discover biomarkers correlated to efficacy or toxicity in common and rare diseases. The difficulty in analyzing the mole of information generated by DMETTM platform led to the development and implementation of algorithms and tools for statistical and data mining analysis. These softwares allow efficient handling of the omics data to validate the explorative SNPs identified by DMET assay and to correlate them with drug efficacy, toxicity and/or cancer susceptibility. In this review we present a suite of bioinformatic frameworks for the preprocessing and analysis of DMET-SNPs data. In particular, we introduce a workflow that uses the GenoMetric Query Language, a high-level query language specifically designed for genomics, able to query public datasets (such as ENCODE, TCGA, GENCODE annotation dataset, etc.) as well as to combine them with private datasets (e.g., output from Affymetrix® DMETTM Platform).

High-Throughput doi: 10.3390/ht9020007

Authors: Rebbeca M. Duar David Kyle Giorgio Casaburi

Over the past century, there has been a steady increase in the stool pH of infants from industrialized countries. Analysis of historical data revealed a strong association between abundance of Bifidobacterium in the gut microbiome of breasted infants and stool pH, suggesting that this taxon plays a key role in determining the pH in the gut. Bifidobacterium longum subsp. infantis is uniquely equipped to metabolize human milk oligosaccharides (HMO) from breastmilk into acidic end products, mainly lactate and acetate. The presence of these acidic compounds in the infant gut is linked to a lower stool pH. Conversely, infants lacking B. infantis have a significantly higher stool pH, carry a higher abundance of potential pathogens and mucus-eroding bacteria in their gut microbiomes, and have signs of chronic enteric inflammation. This suggests the presence of B. infantis and low intestinal pH may be critical to maintaining a protective environment in the infant gut. Here, we summarize recent studies demonstrating that feeding B. infantis EVC001 to breastfed infants results in significantly lower fecal pH compared to controls and propose that low pH is one critical factor in preventing the invasion and overgrowth of harmful bacteria in the infant gut, a process known as colonization resistance.

High-Throughput doi: 10.3390/ht9010006

Authors: Alessio Metere Claire E. Graves

Epigenetics is the interaction between the genome and environmental stimuli capable of influencing gene expression during development and aging. A large number of studies have shown that metabolic diseases are highly associated with epigenetic alterations, suggesting that epigenetic factors may play a central role in obesity. To investigate these relationships, we focus our attention on the most common epigenetic modifications that occur in obesity, including DNA methylation and post-translational modifications of histones. We also consider bariatric surgery as an epigenetic factor, evaluating how the anatomic and physiologic modifications induced by these surgical techniques can change gene expression. Here we discuss the importance of epigenetic mechanisms in chronic disease and cancer, and the role of epigenetic disturbances in obesity, with a focus on the role of bariatric surgery.

High-Throughput doi: 10.3390/ht9010005

Authors: Hovsep Aganyants Pierre Weigel Yeranuhi Hovhannisyan Michèle Lecocq Haykanush Koloyan Artur Hambardzumyan Anichka Hovsepyan Jean-Noël Hallet Vehary Sakanyan

D-hydantoinases catalyze an enantioselective opening of 5- and 6-membered cyclic structures and therefore can be used for the production of optically pure precursors for biomedical applications. The thermostable D-hydantoinase from Geobacillus stearothermophilus ATCC 31783 is a manganese-dependent enzyme and exhibits low activity towards bulky hydantoin derivatives. Homology modeling with a known 3D structure (PDB code: 1K1D) allowed us to identify the amino acids to be mutated at the substrate binding site and in its immediate vicinity to modulate the substrate specificity. Both single and double substituted mutants were generated by site-directed mutagenesis at appropriate sites located inside and outside of the stereochemistry gate loops (SGL) involved in the substrate binding. Substrate specificity and kinetic constant data demonstrate that the replacement of Phe159 and Trp287 with alanine leads to an increase in the enzyme activity towards D,L-5-benzyl and D,L-5-indolylmethyl hydantoins. The length of the side chain and the hydrophobicity of substrates are essential parameters to consider when designing the substrate binding pocket for bulky hydantoins. Our data highlight that D-hydantoinase is the authentic dihydropyrimidinase involved in the pyrimidine reductive catabolic pathway in moderate thermophiles.

High-Throughput doi: 10.3390/ht9010004

Authors: Angela Lombardi Margherita Russo Amalia Luce Floriana Morgillo Virginia Tirino Gabriella Misso Erika Martinelli Teresa Troiani Vincenzo Desiderio Gianpaolo Papaccio Francesco Iovino Giuseppe Argenziano Elvira Moscarella Pasquale Sperlongano Gennaro Galizia Raffaele Addeo Alois Necas Andrea Necasova Fortunato Ciardiello Andrea Ronchi Michele Caraglia Anna Grimaldi

Molecular profiling of a tumor allows the opportunity to design specific therapies which are able to interact only with cancer cells characterized by the accumulation of several genomic aberrations. This study investigates the usefulness of next-generation sequencing (NGS) and mutation-specific analysis methods for the detection of target genes for current therapies in non-small-cell lung cancer (NSCLC), metastatic colorectal cancer (mCRC), and melanoma patients. We focused our attention on EGFR, BRAF, KRAS, and BRAF genes for NSCLC, melanoma, and mCRC samples, respectively. Our study demonstrated that in about 2% of analyzed cases, the two techniques did not show the same or overlapping results. Two patients affected by mCRC resulted in wild-type (WT) for BRAF and two cases with NSCLC were WT for EGFR according to PGM analysis. In contrast, these samples were mutated for the evaluated genes using the therascreen test on Rotor-Gene Q. In conclusion, our experience suggests that it would be appropriate to confirm the WT status of the genes of interest with a more sensitive analysis method to avoid the presence of a small neoplastic clone and drive the clinician to correct patient monitoring.

High-Throughput doi: 10.3390/ht9010003

Authors: Giuseppe Novelli Michela Biancolella Andrea Latini Aldo Spallone Paola Borgiani Marisa Papaluca

The increase in life expectancy during the 20th century ranks as one of society’s greatest achievements, with massive growth in the numbers and proportion of the elderly, virtually occurring in every country of the world. The burden of chronic diseases is one of the main consequences of this phenomenon, severely hampering the quality of life of elderly people and challenging the efficiency and sustainability of healthcare systems. Non-communicable diseases (NCDs) are considered a global emergency responsible for over 70% of deaths worldwide. NCDs are also the basis for complex and multifactorial diseases such as hypertension, diabetes, and obesity. The epidemics of NCDs are a consequence of a complex interaction between health, economic growth, and development. This interaction includes the individual genome, the microbiome, the metabolome, the immune status, and environmental factors such as nutritional and chemical exposure. To counteract NCDs, it is therefore essential to develop an innovative, personalized, preventative, early care model through the integration of different molecular profiles of individuals to identify both the critical biomarkers of NCD susceptibility and to discover novel therapeutic targets.

High-Throughput doi: 10.3390/ht9010002

Authors: High-Throughput Editorial Office High-Throughput Editorial Office

The editorial team greatly appreciates the reviewers who have dedicated their considerable time and expertise to the journal’s rigorous editorial process over the past 12 months, regardless of whether the papers are finally published or not [...]

High-Throughput doi: 10.3390/ht9010001

Authors: Veronica Zelli Chiara Compagnoni Katia Cannita Roberta Capelli Carlo Capalbo Mauro Di Vito Nolfi Edoardo Alesse Francesca Zazzeroni Alessandra Tessitore

Next generation sequencing (NGS) provides a powerful tool in the field of medical genetics, allowing one to perform multi-gene analysis and to sequence entire exomes (WES), transcriptomes or genomes (WGS). The generated high-throughput data are particularly suitable for enhancing the understanding of the genetic bases of complex, multi-gene diseases, such as cancer. Among the various types of tumors, those with a familial predisposition are of great interest for the isolation of novel genes or gene variants, detectable at the germline level and involved in cancer pathogenesis. The identification of novel genetic factors would have great translational value, helping clinicians in defining risk and prevention strategies. In this regard, it is known that the majority of breast/ovarian cases with familial predisposition, lacking variants in the highly penetrant BRCA1 and BRCA2 genes (non-BRCA), remains unexplained, although several less penetrant genes (e.g., ATM, PALB2) have been identified. In this scenario, NGS technologies offer a powerful tool for the discovery of novel factors involved in familial breast/ovarian cancer. In this review, we summarize and discuss the state of the art applications of NGS gene panels, WES and WGS in the context of familial breast/ovarian cancer.

High-Throughput doi: 10.3390/ht8040022

Authors: Matthias Steinbacher Gabriela Alexe Michael Baune Ilya Bobrov Ingmar Bösing Brigitte Clausen Tobias Czotscher Jérémy Epp Andreas Fischer Lasse Langstädtler Daniel Meyer Sachin Raj Menon Oltmann Riemer Heike Sonnenberg Arne Thomann Anastasiya Toenjes Frank Vollertsen Nicole Wielki Nils Ellendt

The development of novel structural materials with increasing mechanical requirements is a very resource-intense process if conventional methods are used. While there are high-throughput methods for the development of functional materials, this is not the case for structural materials. Their mechanical properties are determined by their microstructure, so that increased sample volumes are needed. Furthermore, new short-time characterization techniques are required for individual samples which do not necessarily measure the desired material properties, but descriptors which can later be mapped on material properties. While universal micro-hardness testing is being commonly used, it is limited in its capability to measure sample volumes which contain a characteristic microstructure. We propose to use alternative and fast deformation techniques for spherical micro-samples in combination with classical characterization techniques such as XRD, DSC or micro magnetic methods, which deliver descriptors for the microstructural state.

High-Throughput doi: 10.3390/ht8040021

Authors: Aoife Power Vi Khanh Truong James Chapman Daniel Cozzolino

Compared to traditional laboratory methods, spectroscopic techniques (e.g., near infrared, hyperspectral imaging) provide analysts with an innovative and improved understanding of complex issues by determining several chemical compounds and metabolites at once, allowing for the collection of the sample “fingerprint”. These techniques have the potential to deliver high-throughput options for the analysis of the chemical composition of grapes in the laboratory, the vineyard and before or during harvest, to provide better insights of the chemistry, nutrition and physiology of grapes. Faster computers, the development of software and portable easy to use spectrophotometers and data analytical methods allow for the development of innovative applications of these techniques for the analyses of grape composition.

High-Throughput doi: 10.3390/ht8040020

Authors: Carlos Caicedo-Montoya Laura Pinilla León F. Toro Jeferyd Yepes-García Rigoberto Ríos-Estepa

The performance of software tools for de novo transcriptome assembly greatly depends on the selection of software parameters. Up to now, the development of de novo transcriptome assembly for prokaryotes has not been as remarkable as that for eukaryotes. In this contribution, Rockhopper2 was used to perform a comparative transcriptome analysis of Streptomyces clavuligerus exposed to diverse environmental conditions. The study focused on assessing the incidence of software parameters on software performance for the identification of differentially expressed genes as a final goal. For this, a statistical optimization was performed using the Transrate Assembly Score (TAS). TAS was also used for evaluating the software performance and for comparing it with related tools, e.g., Trinity. Transcriptome redundancy and completeness were also considered for this analysis. Rockhopper2 and Trinity reached a TAS value of 0.55092 and 0.58337, respectively. Trinity assembles transcriptomes with high redundancy, with 55.6% of transcripts having some duplicates. Additionally, we observed that the total number of differentially expressed genes (DEG) and their annotation greatly depends on the method used for removing redundancy and the tools used for transcript quantification. To our knowledge, this is the first work aimed at assessing de novo assembly software for prokaryotic organisms.

High-Throughput doi: 10.3390/ht8040019

Authors: Tyler Weirick Giuseppe Militello Mohammed Rabiul Hosen David John Joseph B. Moore Shizuka Uchida

Studies in epitranscriptomics indicate that RNA is modified by a variety of enzymes. Among these RNA modifications, adenosine to inosine (A-to-I) RNA editing occurs frequently in the mammalian transcriptome. These RNA editing sites can be detected directly from RNA sequencing (RNA-seq) data by examining nucleotide changes from adenosine (A) to guanine (G), which substitutes for inosine (I). However, a careful investigation of such nucleotide changes must be conducted to distinguish sequencing errors and genomic mutations from the genuine editing sites. Building upon our recent introduction of an easy-to-use bioinformatics tool, RNA Editor, to detect RNA editing events from RNA-seq data, we examined the extent by which RNA editing events affect the binding of RNA-binding proteins (RBP). Through employing bioinformatic techniques, we uncovered that RNA editing sites occur frequently in RBP-bound regions. Moreover, the presence of RNA editing sites are more frequent when RNA editing islands were examined, which are regions in which RNA editing sites are present in clusters. When the binding of one RBP, human antigen R [HuR; encoded by ELAV-like protein 1 (ELAV1)], was quantified experimentally, its binding was reduced upon silencing of the RNA editing enzyme adenosine deaminases acting on RNA (ADAR) compared to the control—suggesting that the presence of RNA editing islands influence HuR binding to its target regions. These data indicate RNA editing as an important mediator of RBP–RNA interactions—a mechanism which likely constitutes an additional mode of post-transcription gene regulation in biological systems.

High-Throughput doi: 10.3390/ht8040018

Authors: Hanifeh Seyed Hajizadeh Bahram Heidari Giovanni Bertoldo Maria Cristina Della Lucia Francesco Magro Chiara Broccanello Andrea Baglieri Ivana Puglisi Andrea Squartini Giovanni Campagna Giuseppe Concheri Serenella Nardi Piergiorgio Stevanato

Leonardite-based biostimulants are a large class of compounds, including humic acid substances. Foliar application of biostimulants at field level improves plant growth, yield and quality through metabolic changes and stimulation of plant proton pumps. The present study aimed at identifying optimum dosage of BLACKJAK, a humic acid-based substance, which is able to modify genes involved in sugar beet growth. Thirty-three genes belonging to various biochemical pathway categories were tested in leaves of treated sugar beet (Beta vulgaris L.) samples to assess gene expression profiling in response to BLACKJAK. Seedlings of a diploid and multigerm variety were grown in plastic pots and sprayed with two dilutions of BLACKJAK (dilution 1:500–1.0 mg C L−1 and dilution 1:1000–0.5 mg C L−1). Leaf samples were collected after 24, 48, and 72 h treatment with BLACKJAK for each dilution. RNA was extracted and the quantification of gene expression was performed while using an OpenArray platform. Results of analysis of variance demonstrated that, 15 genes out of a total of 33 genes tested with OpenArray qPCR were significantly affected by treatment and exposure time. Analysis for annotation of gene products and pathways revealed that genes belonging to the mitochondrial respiratory pathways, nitrogen and hormone metabolisms, and nutrient uptake were up-regulated in the BLACKJAK treated samples. Among the up-regulated genes, Bv_PHT2;1 and Bv_GLN1 expression exerted a 2-fold change in 1:1000 and 1:500 BLACKJAK concentrations. Overall, the gene expression data in the BLACKJAK treated leaves demonstrated the induction of plant growth–related genes that were contributed almost to amino acid and nitrogen metabolism, plant defense system, and plant growth.

High-Throughput doi: 10.3390/ht8030017

Authors: Sofia A. Pereira Alexandra M. M. Antunes

Adductomics studies represent effective tools for providing additional insights into how exposure to reactive metabolites can underlie disease mechanisms. This special issue is focused not only on summarizing the analytical methodologies used for DNA, protein, and mercapturic acid adductomics tools but also on highlighting the opportunities and challenges for the application of this type of studies in biomedical research.

High-Throughput doi: 10.3390/ht8020016

Authors: Aeshah A. Raezah Ahmed M. Elaiw Badria S. Alofi

This paper studies the global stability of viral infection models with CTL immune impairment. We incorporate both productively and latently infected cells. The models integrate two routes of transmission, cell-to-cell and virus-to-cell. In the second model, saturated virus–cell and cell–cell incidence rates are considered. The basic reproduction number is derived and two steady states are calculated. We first establish the nonnegativity and boundedness of the solutions of the system, then we investigate the global stability of the steady states. We utilize the Lyapunov method to prove the global stability of the two steady states. We support our theorems by numerical simulations.

High-Throughput doi: 10.3390/ht8020015

Authors: Florencia Villafañez Vanesa Gottifredi Gastón Soria

Post-translational modifications (PTMs) are fundamental traits of protein functionality and their study has been addressed using several approaches over the past years. However, screening methods developed to detect regulators of PTMs imply many challenges and are usually based on expensive techniques. Herein, we described the development and optimization of a western blot-based platform for identification of regulators of a specific PTM—mono-ubiquitylation of proliferating cell nuclear antigen (PCNA). This cell-based method does not require specific equipment, apart from the basic western blot (WB) devices and minor accessories, which are accessible for most research labs. The modifications introduced to the classical WB protocol allow the performance of PTM analysis from a single well of a 96-well plate with minimal sample manipulation and low intra- and inter-plate variability, making this method ideal to screen arrayed compound libraries in a 96-well format. As such, our experimental pipeline provides the proof of concept to design small screenings of PTM regulators by improving the quantitative accuracy and throughput capacity of classical western blots.

High-Throughput doi: 10.3390/ht8020014

Authors: Lara A. Heersema Hugh D. C. Smyth

There is a current need to develop and optimize new therapeutics for the treatment of dental caries, but these efforts are limited by the relatively low throughput of relevant in vitro models. The aim of this work was to bridge the 96-well microtiter plate system with a relevant multispecies dental caries model that could be reproducibly grown to allow for the high-throughput screening of anti-biofilm therapies. Various media and inoculum concentrations were assessed using metabolic activity, biomass, viability, and acidity assays to determine the optimal laboratory-controlled conditions for a multispecies biofilm composed of Streptococcus gordonii, Streptococcus mutans, and Candida albicans. The selected model encompasses several of the known fundamental characteristics of dental caries-associated biofilms. The 1:1 RPMI:TSBYE 0.6% media supported the viability and biomass production of mono- and multispecies biofilms best. Kinetic studies over 48 h in 1:1 RPMI:TSBYE 0.6% demonstrated a stable biofilm phase between 10 and 48 h for all mono- and multispecies biofilms. The 1:1:0.1 S. gordonii: S. mutans: C. albicans multispecies biofilm in 1:1 RPMI:TSBYE 0.6% is an excellent choice for a high-throughput multispecies model of dental caries. This high-throughput multispecies model can be used for screening novel therapies and for better understanding the treatment effects on biofilm interactions and stability.

High-Throughput doi: 10.3390/ht8020013

Authors: Jingshu Guo Robert J. Turesky

The measurement of DNA adducts, the covalent modifications of DNA upon the exposure to the environmental and dietary genotoxicants and endogenously produced electrophiles, provides molecular evidence for DNA damage. With the recent improvements in the sensitivity and scanning speed of mass spectrometry (MS) instrumentation, particularly high-resolution MS, it is now feasible to screen for the totality of DNA damage in the human genome through DNA adductomics approaches. Several MS platforms have been used in DNA adductomic analysis, each of which has its strengths and limitations. The loss of 2′-deoxyribose from the modified nucleoside upon collision-induced dissociation is the main transition feature utilized in the screening of DNA adducts. Several advanced data-dependent and data-independent scanning techniques originated from proteomics and metabolomics have been tailored for DNA adductomics. The field of DNA adductomics is an emerging technology in human exposure assessment. As the analytical technology matures and bioinformatics tools become available for analysis of the MS data, DNA adductomics can advance our understanding about the role of chemical exposures in DNA damage and disease risk.

High-Throughput doi: 10.3390/ht8020012

Authors: Wenzhao Bi Geeng-Fu Jang Lei Zhang John W. Crabb James Laird Mikhail Linetsky Robert G. Salomon

Isoprostane endoperoxides generated by free radical-induced oxidation of arachidonates, and prostaglandin endoperoxides generated through enzymatic cyclooxygenation of arachidonate, rearrange nonenzymatically to isoprostanes and a family of stereo and structurally isomeric γ-ketoaldehyde seco-isoprostanes, collectively known as isolevuglandins (isoLGs). IsoLGs are stealthy toxins, and free isoLGs are not detected in vivo. Rather, covalent adducts are found to incorporate lysyl ε-amino residues of proteins or ethanolamino residues of phospholipids. In vitro studies have revealed that adduction occurs within seconds and is uniquely prone to cause protein–protein crosslinks. IsoLGs accelerate the formation of the type of amyloid beta oligomers that have been associated with neurotoxicity. Under air, isoLG-derived pyrroles generated initially are readily oxidized to lactams and undergo rapid oxidative coupling to pyrrole–pyrrole crosslinked dimers, and to more highly oxygenated derivatives of those dimers. We have now found that pure isoLG-derived pyrroles, which can be generated under anoxic conditions, do not readily undergo oxidative coupling. Rather, dimer formation only occurs after an induction period by an autocatalytic oxidative coupling. The stable free-radical TEMPO abolishes the induction period, catalyzing rapid oxidative coupling. The amine N-oxide TMAO is similarly effective in catalyzing the oxidative coupling of isoLG pyrroles. N-acetylcysteine abolishes the generation of pyrrole–pyrrole crosslinks. Instead pyrrole-cysteine adducts are produced. Two unified single-electron transfer mechanisms are proposed for crosslink and pyrrole-cysteine adduct formation from isoLG-pyrroles, as well as for their oxidation to lactams and hydroxylactams.

High-Throughput doi: 10.3390/ht8020011

Authors: Timm Schwaar Maike Lettow Dario Remmler Hans G. Börner Michael G. Weller

Screening of one-bead-one-compound (OBOC) libraries is a proven procedure for the identification of protein-binding ligands. The demand for binders with high affinity and specificity towards various targets has surged in the biomedical and pharmaceutical field in recent years. The traditional peptide screening involves tedious steps such as affinity selection, bead picking, sequencing, and characterization. Herein, we present a high-throughput “all-on-one chip” system to avoid slow and technically complex bead picking steps. On a traditional glass slide provided with an electrically conductive tape, beads of a combinatorial peptide library are aligned and immobilized by application of a precision sieve. Subsequently, the chip is incubated with a fluorophore-labeled target protein. In a fluorescence scan followed by matrix-assisted laser desorption/ionization (MALDI)-time of flight (TOF) mass spectrometry, high-affinity binders are directly and unambiguously sequenced with high accuracy without picking of the positive beads. The use of an optimized ladder sequencing approach improved the accuracy of the de-novo sequencing step to nearly 100%. The new technique was validated by employing a FLAG-based model system, identifying new peptide binders for the monoclonal M2 anti-FLAG antibody, and was finally utilized to search for IgG-binding peptides. In the present format, more than 30,000 beads can be screened on one slide.

High-Throughput doi: 10.3390/ht8020010

Authors: Clara Gonçalves-Dias Judit Morello Valdir Semedo M. João Correia Nuno R. Coelho Emilia C. Monteiro Alexandra M. M. Antunes Sofia A. Pereira

The mercapturate pathway is a unique metabolic circuitry that detoxifies electrophiles upon adducts formation with glutathione. Since its discovery over a century ago, most of the knowledge on the mercapturate pathway has been provided from biomonitoring studies on environmental exposure to toxicants. However, the mercapturate pathway-related metabolites that is formed in humans—the mercapturomic profile—in health and disease is yet to be established. In this paper, we put forward the hypothesis that these metabolites are key pathophysiologic factors behind the onset and development of non-communicable chronic inflammatory diseases. This review goes from the evidence in the formation of endogenous metabolites undergoing the mercapturate pathway to the methodologies for their assessment and their association with cancer and respiratory, neurologic and cardiometabolic diseases.

High-Throughput doi: 10.3390/ht8020009

Authors: João Nunes Catarina Charneira Judit Morello João Rodrigues Sofia A. Pereira Alexandra M. M. Antunes

Protein covalent adducts formed upon exposure to reactive (mainly electrophilic) chemicals may lead to the development of a wide range of deleterious health outcomes. Therefore, the identification of protein covalent adducts constitutes a huge opportunity for a better understanding of events underlying diseases and for the development of biomarkers which may constitute effective tools for disease diagnosis/prognosis, for the application of personalized medicine approaches and for accurately assessing human exposure to chemical toxicants. The currently available mass spectrometry (MS)-based methodologies, are clearly the most suitable for the analysis of protein covalent modifications, providing accuracy, sensitivity, unbiased identification of the modified residue and conjugates along with quantitative information. However, despite the huge technological advances in MS instrumentation and bioinformatics tools, the identification of low abundant protein covalent adducts is still challenging. This review is aimed at summarizing the MS-based methodologies currently used for the identification of protein covalent adducts and the strategies developed to overcome the analytical challenges, involving not only sample pre-treatment procedures but also distinct MS and data analysis approaches.

High-Throughput doi: 10.3390/ht8020008

Authors: Nelson Perdigão Agostinho Rosa

The dark proteome, as we define it, is the part of the proteome where 3D structure has not been observed either by homology modeling or by experimental characterization in the protein universe. From the 550.116 proteins available in Swiss-Prot (as of July 2016), 43.2% of the eukarya universe and 49.2% of the virus universe are part of the dark proteome. In bacteria and archaea, the percentage of the dark proteome presence is significantly less, at 12.6% and 13.3% respectively. In this work, we present a necessary step to complete the dark proteome picture by introducing the map of the dark proteome in the human and in other model organisms of special importance to mankind. The most significant result is that around 40% to 50% of the proteome of these organisms are still in the dark, where the higher percentages belong to higher eukaryotes (mouse and human organisms). Due to the amount of darkness present in the human organism being more than 50%, deeper studies were made, including the identification of ‘dark’ genes that are responsible for the production of so-called dark proteins, as well as the identification of the ‘dark’ tissues where dark proteins are over represented, namely, the heart, cervical mucosa, and natural killer cells. This is a step forward in the direction of gaining a deeper knowledge of the human dark proteome.

High-Throughput doi: 10.3390/ht8020007

Authors: Andrea Palermo Richard Thelen Laura Weber Tobias Foertsch Simone Rentschler Verena Hackert Julia Syurik Alexander Nesterov-Mueller

Peptide microarrays are a fast-developing field enabling the mapping of linear epitopes in the immune response to vaccinations or diseases and high throughput studying of protein-protein interactions. In this respect, a rapid label-free measurement of protein layer topographies in the array format is of great interest but is also a great challenge due to the extremely low aspect ratios of the peptide spots. We have demonstrated the potential of vertical scanning interferometry (VSI) for a detailed morphological analysis of peptide arrays and binding antibodies. The VSI technique is shown to scan an array area of 5.1 square millimeters within 3–4 min at a resolution of 1.4 μm lateral and 0.1 nm vertical in the full automation mode. Topographies obtained by VSI do match the one obtained by AFM measurements, demonstrating the accuracy of the technique. A detailed topology of peptide-antibody layers on single spots was measured. Two different measurement regions are distinguished according to the antibody concentration. In the case of weakly diluted serum, the thickness of the antibody layer is independent of the serum dilution and corresponds to the physical thickness of the accumulated antibody layer. In strongly diluted serum, the thickness measured via VSI is linearly proportional to the serum dilution.

High-Throughput doi: 10.3390/ht8010006

Authors: Henrik Carlsson Stephen M. Rappaport Margareta Törnqvist

The reaction products of electrophiles in vivo can be measured as adducts to the abundant proteins, hemoglobin (Hb), and human serum albumin (HSA), in human blood samples. During the last decade, methods for untargeted screening of such adducts, called “adductomics”, have used liquid chromatography-mass spectrometry to detect large numbers of previously unknown Hb and HSA adducts. This review presents methodologies that were developed and used in our laboratories for Hb and HSA adductomics, respectively. We discuss critical aspects regarding choice of target protein, sample preparation, mass spectrometry, data evaluation, and strategies for identification of detected unknown adducts. With this review we give an overview of these two methodologies used for protein adductomics and the precursor electrophiles that have been elucidated from the adducts.

High-Throughput doi: 10.3390/ht8010005

Authors: Maddalena Cagnone Davide Piloni Ilaria Ferrarotti Monica Di Venere Simona Viglio Sara Magni Anna Bardoni Roberta Salvini Marco Fumagalli Paolo Iadarola Sabrina Martinello Federica Meloni

The neutrophilic component in bronchiolitis obliterans syndrome (BOS, the main form of chronic lung rejection), plays a crucial role in the pathogenesis and maintenance of the disorder. Human Neutrophil Elastase (HNE), a serine protease responsible of elastin degradation whose action is counteracted by α1-antitrypsin (AAT), a serum inhibitor specific for this protease. This work aimed to investigate the relationship between HNE and AAT in bronchoalveolar lavage fluid (BALf) from stable lung transplant recipients and BOS patients to understand whether the imbalance between proteases and inhibitors is relevant to the development of BOS. To reach this goal a multidisciplinary procedure was applied which included: (i) the use of electrophoresis/western blotting coupled with liquid chromatography-mass spectrometric analysis; (ii) the functional evaluation of the residual antiprotease activity, and (iii) a neutrophil count. The results of these experiments demonstrated, for the first time, the presence of the complex between HNE and AAT in a number of BALf samples. The lack of this complex in a few specimens analyzed was investigated in relation to a patient’s lung inflammation. The neutrophil count and the determination of HNE and AAT activities allowed us to speculate that the presence of the complex correlated with the level of lung inflammation.

High-Throughput doi: 10.3390/ht8010004

Authors: Cen Wu Fei Zhou Jie Ren Xiaoxi Li Yu Jiang Shuangge Ma

High-throughput technologies have been used to generate a large amount of omics data. In the past, single-level analysis has been extensively conducted where the omics measurements at different levels, including mRNA, microRNA, CNV and DNA methylation, are analyzed separately. As the molecular complexity of disease etiology exists at all different levels, integrative analysis offers an effective way to borrow strength across multi-level omics data and can be more powerful than single level analysis. In this article, we focus on reviewing existing multi-omics integration studies by paying special attention to variable selection methods. We first summarize published reviews on integrating multi-level omics data. Next, after a brief overview on variable selection methods, we review existing supervised, semi-supervised and unsupervised integrative analyses within parallel and hierarchical integration studies, respectively. The strength and limitations of the methods are discussed in detail. No existing integration method can dominate the rest. The computation aspects are also investigated. The review concludes with possible limitations and future directions for multi-level omics data integration.

High-Throughput doi: 10.3390/ht8010003

Authors: High-Throughput Editorial Office High-Throughput Editorial Office

Rigorous peer-review is the corner-stone of high-quality academic publishing [...]

High-Throughput doi: 10.3390/ht8010002

Authors: Benita C. Percival Martin Grootveld Miles Gibson Yasan Osman Marco Molinari Fereshteh Jafari Tarsem Sahota Mark Martin Federico Casanova Melissa L. Mather Mark Edgar Jinit Masania Philippe B. Wilson

Novel sensing technologies for liquid biopsies offer promising prospects for the early detection of metabolic conditions through omics techniques. Indeed, high-field nuclear magnetic resonance (NMR) facilities are routinely used for metabolomics investigations on a range of biofluids in order to rapidly recognise unusual metabolic patterns in patients suffering from a range of diseases. However, these techniques are restricted by the prohibitively large size and cost of such facilities, suggesting a possible role for smaller, low-field NMR instruments in biofluid analysis. Herein we describe selected biomolecule validation on a low-field benchtop NMR spectrometer (60 MHz), and present an associated protocol for the analysis of biofluids on compact NMR instruments. We successfully detect common markers of diabetic control at low-to-medium concentrations through optimised experiments, including α-glucose (≤2.8 mmol/L) and acetone (25 µmol/L), and additionally in readily accessible biofluids, particularly human urine. We present a combined protocol for the analysis of these biofluids with low-field NMR spectrometers for metabolomics applications, and offer a perspective on the future of this technique appealing to ‘point-of-care’ applications.

High-Throughput doi: 10.3390/ht8010001

Authors: Minal B. Patel Jun Wang

In the need to characterise the genomic landscape of cancers and to establish novel biomarkers and therapeutic targets, studies have largely focused on the identification of driver mutations within the protein-coding gene regions, where the most pathogenic alterations are known to occur. However, the noncoding genome is significantly larger than its protein-coding counterpart, and evidence reveals that regulatory sequences also harbour functional mutations that significantly affect the regulation of genes and pathways implicated in cancer. Due to the sheer number of noncoding mutations (NCMs) and the limited knowledge of regulatory element functionality in cancer genomes, differentiating pathogenic mutations from background passenger noise is particularly challenging technically and computationally. Here we review various up-to-date high-throughput sequencing data/studies and in silico methods that can be employed to interrogate the noncoding genome. We aim to provide an overview of available data resources as well as computational and molecular techniques that can help and guide the search for functional NCMs in cancer genomes.

High-Throughput doi: 10.3390/ht7040040

Authors: Mariamena Arbitrio Maria Teresa Di Martino Francesca Scionti Vito Barbieri Licia Pensabene Pierosandro Tagliaferri

In the past decades, many efforts have been made to individualize medical treatments, taking into account molecular profiles and the individual genetic background. The development of molecularly targeted drugs and immunotherapy have revolutionized medical treatments but the inter-patient variability in the anti-tumor drug pharmacokinetics (PK) and pharmacodynamics can be explained, at least in part, by genetic variations in genes encoding drug metabolizing enzymes and transporters (ADME) or in genes encoding drug receptors. Here, we focus on high-throughput technologies applied for PK screening for the identification of predictive biomarkers of efficacy or toxicity in cancer treatment, whose application in clinical practice could promote personalized treatments tailored on individual’s genetic make-up. Pharmacogenomic tools have been implemented and the clinical utility of pharmacogenetic screening could increase safety in patients for the identification of drug metabolism-related biomarkers for a personalized medicine. Although pharmacogenomic studies were performed in adult cohorts, pharmacogenetic pediatric research has yielded promising results. Additionally, we discuss the current challenges and theoretical bases for the implementation of pharmacogenetic tests for translation in the clinical practice taking into account that pharmacogenomics platforms are discovery oriented and must open the way for the setting of robust tests suitable for daily practice.

High-Throughput doi: 10.3390/ht7040039

Authors: Atif A. Ahmed Divya S. Vundamati Midhat S. Farooqi Erin Guest

Precision oncologic medicine is an emerging approach for cancer treatment that has recently taken giant steps in solid clinical practice. Recent advances in molecular diagnostics that can analyze the individual tumor’s variability in genes have provided greater understanding and additional strategies to treat cancers. Although tumors can be tested by several molecular methods, the use of next-generation sequencing (NGS) has greatly facilitated our understanding of pediatric cancer and identified additional therapeutic opportunities. Pediatric tumors have a different genetic make-up, with a fewer number of actionable targets than adult tumors. Nevertheless, precision oncology in the pediatric population has greatly improved the survival of patients with leukemia and solid tumors. This review discusses the current status of pediatric precision oncology and the different clinical scenarios in which it can be effectively applied.

High-Throughput doi: 10.3390/ht7040038

Authors: Valeria D’Argenio

The last few years have featured an increasing interest in the study of the human microbiome and its correlations with health status. Indeed, technological advances have allowed the study of microbial communities to reach a previously unthinkable sensitivity, showing the presence of microbes also in environments usually considered as sterile. In this scenario, microbial communities have been described in the amniotic fluid, the umbilical blood cord, and the placenta, denying a dogma of reproductive medicine that considers the uterus like a sterile womb. This prenatal microbiome may play a role not only in fetal development but also in the predisposition to diseases that may develop later in life, and also in adulthood. Thus, the aim of this review is to report the current knowledge regarding the prenatal microbiome composition, its association with pathological processes, and the future perspectives regarding its manipulation for healthy status promotion and maintenance.

High-Throughput doi: 10.3390/ht7040037

Authors: Theodoros G. Soldatos Guillaume Taglang David B. Jackson

We present a novel approach for the molecular transformation and analysis of patient clinical phenotypes. Building on the fact that drugs perturb the function of targets/genes, we integrated data from 8.2 million clinical reports detailing drug-induced side effects with the molecular world of drug-target information. Using this dataset, we extracted 1.8 million associations of clinical phenotypes to 770 human drug-targets. This collection is perhaps the largest phenotypic profiling reference of human targets to-date, and unique in that it enables rapid development of testable molecular hypotheses directly from human-specific information. We also present validation results demonstrating analytical utilities of the approach, including drug safety prediction, and the design of novel combination therapies. Challenging the long-standing notion that molecular perturbation studies cannot be performed in humans, our data allows researchers to capitalize on the vast tomes of clinical information available throughout the healthcare system.

High-Throughput doi: 10.3390/ht7040036

Authors: Rosalino Vázquez-López Sandra Solano-Gálvez Bertha A. León-Chávez María R. Thompson-Bonilla Tayde Guerrero-González Eduardo Gómez-Conde Daniel Martínez-Fong Juan A. González-Barrios

Beta-lactam resistant bacteria, which are commonly resident in tertiary hospitals, have emerged as a worldwide health problem because of ready-to-eat vegetable intake. We aimed to characterize the genes that provide resistance to beta-lactam antibiotics in Enterobacteriaceae, isolated from five commercial salad brands for human consumption in Mexico City. In total, twenty-five samples were collected, grown in blood agar plates, and the bacteria were biochemistry identified and antimicrobial susceptibility testing was done. The carried family genes were identified by endpoint PCR and the specific genes were confirmed with whole genome sequencing (WGS) by Next Generation Sequencing (NGS). Twelve positive cultures were identified and their microbiological distribution was as follows: 8.3% for Enterobacter aerogene (n = 1), 8.3% for Serratia fonticola (n = 1), 16.7% for Serratia marcesens (n = 2), 16.7% for Klebsiella pneumoniae (n = 2), and 50% (n = 6) for Enterobacter cloacae. The endpoint PCR results showed 11 colonies positive for blaBIL (91.7%), 11 for blaSHV (91.7%), 11 for blaCTX (97.7%), 12 for blaDHA (100%), four for blaVIM (33.3%), two for blaOXA (16.7%), two for blaIMP (16.7%), one for blaKPC (8.3%), and one for blaTEM (8.3%) gen; all samples were negative for blaROB, blaCMY, blaP, blaCFX and blaLAP gene. The sequencing analysis revealed a specific genotype for Enterobacter cloacae (blaSHV-12, blaCTX-M-15, blaDHA-1, blaKPC-2); Serratia marcescens (blaSHV-1, blaCTX-M-3, blaDHA-1, blaVIM-2); Klebsiella pneumoniae (blaSHV-12, blaCTX-M-15, blaDHA-1); Serratia fonticola (blaSHV-12, blaVIM-1, blaDHA-1); and, Enterobacter aerogene (blaSHV-1, blaCTX-M-1, blaDHA-1, blaVIM-2, blaOXA-9). Our results indicate that beta-lactam-resistant bacteria have acquired integrons with a different number of genes that provide pan-resistance to beta-lactam antibiotics, including penicillins, oxacillins, cefalosporins, monobactams, carbapenems, and imipenems.

High-Throughput doi: 10.3390/ht7040035

Authors: Jaouad Danane Karam Allali

We model the transmission of the hepatitis B virus (HBV) by six differential equations that represent the reactions between HBV with DNA-containing capsids, the hepatocytes, the antibodies and the cytotoxic T-lymphocyte (CTL) cells. The intracellular delay and treatment are integrated into the model. The existence of the optimal control pair is supported and the characterization of this pair is given by the Pontryagin’s minimum principle. Note that one of them describes the effectiveness of medical treatment in restraining viral production, while the second stands for the success of drug treatment in blocking new infections. Using the finite difference approximation, the optimality system is derived and solved numerically. Finally, the numerical simulations are illustrated in order to determine the role of optimal treatment in preventing viral replication.

High-Throughput doi: 10.3390/ht7040034

Authors: Linda Minotti Chiara Agnoletto Federica Baldassari Fabio Corrà Stefano Volinia

In the last decade, it has been demonstrated that long non-coding RNAs (lncRNAs) are involved in cancer development. The great majority of studies on lncRNAs report alterations, principally on their expression profiles, in several tumor types with respect to the normal tissues of origin. Conversely, since lncRNAs constitute a relatively novel class of RNAs compared to protein-coding transcripts (mRNAs), the landscape of their mutations and variations has not yet been extensively studied. However, in recent years an ever-increasing number of articles have described mutations of lncRNAs. Single-nucleotide polymorphisms (SNPs) that occur within the lncRNA transcripts can affect the structure and function of these RNA molecules, while the presence of a SNP in the promoter region of a lncRNA could alter its expression level. Also, somatic mutations that occur within lncRNAs have been shown to exert important effects in cancer and preliminary data are promising. Overall, the evidence suggests that SNPs and somatic mutation on lncRNAs may play a role in the pathogenesis of cancer, and indicates strong potential for further development of lncRNAs as biomarkers.

High-Throughput doi: 10.3390/ht7040033

Authors: Maria Eugenia Gallo Cantafio Katia Grillone Daniele Caracciolo Francesca Scionti Mariamena Arbitrio Vito Barbieri Licia Pensabene Pietro Hiram Guzzi Maria Teresa Di Martino

Integration of multi-omics data from different molecular levels with clinical data, as well as epidemiologic risk factors, represents an accurate and promising methodology to understand the complexity of biological systems of human diseases, including cancer. By the extensive use of novel technologic platforms, a large number of multidimensional data can be derived from analysis of health and disease systems. Comprehensive analysis of multi-omics data in an integrated framework, which includes cumulative effects in the context of biological pathways, is therefore eagerly awaited. This strategy could allow the identification of pathway-addiction of cancer cells that may be amenable to therapeutic intervention. However, translation into clinical settings requires an optimized integration of omics data with clinical vision to fully exploit precision cancer medicine. We will discuss the available technical approach and more recent developments in the specific field.

High-Throughput doi: 10.3390/ht7040032

Authors: Stephanie A. Bannister Stephen P. Kidd Elizabeth Kirby Sonal Shah Anvy Thomas Richard Vipond Michael J. Elmore Andrew Telfer Brunton Peter Marsh Steve Green Nigel J. Silman Karen E. Kempsell

Meningitis is commonly caused by infection with a variety of bacterial or viral pathogens. Acute bacterial meningitis (ABM) can cause severe disease, which can progress rapidly to a critical life-threatening condition. Rapid diagnosis of ABM is critical, as this is most commonly associated with severe sequelae with associated high mortality and morbidity rates compared to viral meningitis, which is less severe and self-limiting. We have designed a microarray for detection and diagnosis of ABM. This has been validated using randomly amplified DNA targets (RADT), comparing buffers with or without formamide, in glass slide format or on the Alere ArrayTubeTM (Alere Technologies GmbH) microarray platform. Pathogen-specific signals were observed using purified bacterial nucleic acids and to a lesser extent using patient cerebral spinal fluid (CSF) samples, with some technical issues observed using RADT and glass slides. Repurposing the array onto the Alere ArrayTubeTM platform and using a targeted amplification system increased specific and reduced nonspecific hybridization signals using both pathogen nucleic and patient CSF DNA targets, better revealing pathogen-specific signals although sensitivity was still reduced in the latter. This diagnostic microarray is useful as a laboratory diagnostic tool for species and strain designation for ABM, rather than for primary diagnosis.

High-Throughput doi: 10.3390/ht7040031

Authors: Radhey S. Gupta

An alarming increase in tuberculosis (TB) caused by drug-resistant strains of Mycobacterium tuberculosis has created an urgent need for new antituberculosis drugs acting via novel mechanisms. Phylogenomic and comparative genomic analyses reviewed here reveal that the TB causing bacteria comprise a small group of organisms differing from all other mycobacteria in numerous regards. Comprehensive analyses of protein sequences from mycobacterial genomes have identified 63 conserved signature inserts and deletions (indels) (CSIs) in important proteins that are distinctive characteristics of the TB-complex of bacteria. The identified CSIs provide potential means for development of novel diagnostics as well as therapeutics for the TB-complex of bacteria based on four key observations: (i) The CSIs exhibit a high degree of exclusivity towards the TB-complex of bacteria; (ii) Earlier work on CSIs provide evidence that they play important/essential functions in the organisms for which they exhibit specificity; (iii) CSIs are located in surface-exposed loops of the proteins implicated in mediating novel interactions; (iv) Homologs of the CSIs containing proteins, or the CSIs in such homologs, are generally not found in humans. Based on these characteristics, it is hypothesized that the high-throughput virtual screening for compounds binding specifically to the CSIs (or CSI containing regions) and thereby inhibiting the cellular functions of the CSIs could lead to the discovery of a novel class of drugs specifically targeting the TB-complex of organisms.

High-Throughput doi: 10.3390/ht7040030

Authors: Ioannis A. Voutsadakis

CTCF (CCCTC-binding factor) is a transcription regulator with hundreds of binding sites in the human genome. It has a main function as an insulator protein, defining together with cohesins the boundaries of areas of the genome called topologically associating domains (TADs). TADs contain regulatory elements such as enhancers which function as regulators of the transcription of genes inside the boundaries of the TAD while they are restricted from regulating genes outside these boundaries. This paper will examine the most common genetic lesions of CTCF as well as its related protein CTCFL (CTCF-like also called BORIS) in cancer using publicly available data from published genomic studies. Cancer types where abnormalities in the two genes are more common will be examined for possible associations with underlying repair defects or other prevalent genetic lesions. The putative functional effects in CTCF and CTCFL lesions will also be explored.

High-Throughput doi: 10.3390/ht7040029

Authors: Yee Tze Ung Chin Eng Ong Yan Pan

Cytochrome P450 (CYP) is a critical drug-metabolizing enzyme superfamily. Modulation of CYP enzyme activities has the potential to cause drug–drug/herb interactions. Drug–drug/herb interactions can lead to serious adverse drug reactions (ADRs) or drug failures. Therefore, there is a need to examine the modulatory effects of new drug entities or herbal preparations on a wide range of CYP isoforms. The classic method of quantifying CYP enzyme activities is based on high-performance liquid chromatography (HPLC), which is time- and reagent-consuming. In the past two decades, high-throughput screening methods including fluorescence-based, luminescence-based, and mass-spectrometry-based assays have been developed and widely applied to estimate CYP enzyme activities. In general, these methods are faster and use lower volume of reagents than HPLC. However, each high-throughput method has its own limitations. Investigators may make a selection of these methods based on the available equipment in the laboratory, budget, and enzyme sources supplied. Furthermore, the current high-throughput systems should look into developing a reliable automation mechanism to accomplish ultra-high-throughput screening in the near future.

High-Throughput doi: 10.3390/ht7030028

Authors: Francesca Scionti Maria Teresa Di Martino Licia Pensabene Valentina Bruni Daniela Concolino

Submicroscopic chromosomal copy number variations (CNVs), such as deletions and duplications, account for about 15–20% of patients affected with developmental delay, intellectual disability, multiple congenital anomalies, and autism spectrum disorder. Most of CNVs are de novo or inherited rearrangements with clinical relevance, but there are also rare inherited imbalances with unknown significance that make difficult the clinical management and genetic counselling. Chromosomal microarrays analysis (CMA) are recognized as the first-line test for CNV detection and are now routinely used in the clinical diagnostic laboratory. The recent use of CMA platforms that combine classic copy number analysis with single-nucleotide polymorphism (SNP) genotyping has increased the diagnostic yields. Here we discuss the application of the Cytoscan high-density (HD) SNP-array for the detection of CNVs. We provide an overview of molecular analyses involved in identifying pathogenic CNVs and highlight important guidelines to establish pathogenicity of CNV.

High-Throughput doi: 10.3390/ht7030027

Authors: Afshan Masood Hicham Benabdelkamel Assim A. Alfadda

Proteomics has become one of the most important disciplines for characterizing cellular protein composition, building functional linkages between protein molecules, and providing insight into the mechanisms of biological processes in a high-throughput manner. Mass spectrometry-based proteomic advances have made it possible to study human diseases, including obesity, through the identification and biochemical characterization of alterations in proteins that are associated with it and its comorbidities. A sizeable number of proteomic studies have used the combination of large-scale separation techniques, such as high-resolution two-dimensional gel electrophoresis or liquid chromatography in combination with mass spectrometry, for high-throughput protein identification. These studies have applied proteomics to comprehensive biochemical profiling and comparison studies while using different tissues and biological fluids from patients to demonstrate the physiological or pathological adaptations within their proteomes. Further investigations into these proteome-wide alterations will enable us to not only understand the disease pathophysiology, but also to determine signature proteins that can serve as biomarkers for obesity and related diseases. This review examines the different proteomic techniques used to study human obesity and discusses its successful applications along with its technical limitations.

High-Throughput doi: 10.3390/ht7030026

Authors: Gabina Calderón-Rosete Juan Antonio González-Barrios Manuel Lara-Lozano Celia Piña-Leyva Leonardo Rodríguez-Sosa

The freshwater crayfish Procambarus clarkii is an animal model employed for physiological and immunological studies and is also of great economic importance in aquaculture. Although it is a species of easy husbandry, a high percentage of its production is lost annually as a result of infectious diseases. Currently, genetic information about the immune system of crustaceans is limited. Therefore, we used the abdominal nerve cord from P. clarkii to obtain its transcriptome using Next Generation Sequencing (NGS) to identify proteins that participate in the immune system. The reads were assembled de novo and consensus sequences with more than 3000 nucleotides were selected for analysis. The transcripts of the sequences of RNA were edited for annotation and sent to the GenBank database of the National Center for Biotechnology Information (NCBI). We made a list of accession numbers of the sequences which were organized by the putative role of the immune system pathway in which they participate. In this work, we report on 80 proteins identified from the transcriptome of crayfish related to the immune system, 74 of them being the first reported for P. clarkii. We hope that the knowledge of these sequences will contribute significantly to the development of future studies of the immune system in crustaceans.

High-Throughput doi: 10.3390/ht7030025

Authors: Mariel Gullian Klanian Mariana Delgadillo Díaz Maria José Sánchez Solís

The present study aimed at determining the histamine production capacity of Gram (+) and Gram (−) bacteria isolated from Octopus maya, along with identifying the presence of amino acid decarboxylase genes. Of the total 80 psychrotrophic microorganisms, 32 strains were identified as histamine-forming bacteria. The recombinant DNA technique was used for genotypic identification of histidine (hdc), ornithine (odc), and lysine decarboxylases (ldc) genes. Thirty-two strains were able to produce 60–100 ppm in trypticase soy broth with 1.0% l-histidine after 6 h at 20 °C. NR6B showed 98% homology with Hafnia alvei. NR73 represented 18.8% of the total isolates and showed 98% homology with Enterobacter xianfengensis and Enterobacter cloacae. NR6A represented 6% of the total isolates, which were identified as Lactococcus sp. The hdc gen from NR6B showed 100% identity with hdc from Morganella morganii; ldc showed 97.7% identity with ldc from Citrobacter freundii. The Odc gene was detected only in NR73 and showed 100% identity with Enterobacter sp. All the isolated were identified as weak histamine–former. The ingestion of a food containing small amounts of histamine has little effect on humans; however, the formation of biogenic amines is often considered as an indicator of hygienic quality; this emphasizes the importance of improving good management practices and storage.

High-Throughput doi: 10.3390/ht7030024

Authors: Daniela Berger Aviva Rakhamimova Andrew Pollack Zvi Loewy

The oral cavity harbors hundreds of microbial species that are present either as planktonic cells or incorporated into biofilms. The majority of the oral microbes are commensal organisms. Those that are pathogenic microbes can result in oral infections, and at times can initiate systemic diseases. Biofilms that contain pathogens are challenging to control. Many conventional antimicrobials have proven to be ineffective. Recent advances in science and technology are providing new approaches for pathogen control and containment and methods to characterize biofilms. This perspective provides (1) a general understanding of biofilm development; (2) a description of emerging chemical and biological methods to control oral biofilms; and (3) an overview of high-throughput analytical approaches to analyze biofilms.

High-Throughput doi: 10.3390/ht7030023

Authors: Patrick Breheny Arnold Stromberg Joshua Lambert

It is increasingly common for experiments in biology and medicine to involve large numbers of hypothesis tests. A natural graphical method for visualizing these tests is to construct a histogram from the p-values of these tests. In this article, we examine the shapes, both regular and irregular, that these histograms can take on, as well as present simple inferential procedures that help to interpret the shapes in terms of diagnosing potential problems with the experiment. We examine potential causes of these problems in detail, and discuss potential remedies. Throughout, examples of irregular-looking p-value histograms are provided and based on case studies involving real biological experiments.

High-Throughput doi: 10.3390/ht7030022

Authors: Massimo Pitorri Marco Franceschin Ilaria Serafini Alessandro Ciccòla Claudio Frezza Armandodoriano Bianco

This paper reports on the modification of two synthetic steps in the usual protocol used for obtaining EMICORON. EMICORON is a benzo[ghi]perylen-diimide, which was synthesized for the first time in our laboratory in 2012, and has shown to have in vivo antitumor activities that interferes with the tumor growth and development using a multi-target mechanism of action. The provided modifications, which involved the reaction times, the reaction conditions, and the work-up procedures, allowed the global yield of the process to be increased from 28% to about 40%. Thus, this new procedure may be more suitable for recovering higher amounts of EMICORON to be used in further preclinical studies.

High-Throughput doi: 10.3390/ht7030021

Authors: Nur Nadia Razali Nur Hafizah Hashim Adam Thean Chor Leow Abu Bakar Salleh

A functional mini protein can be developed by miniaturising its size. The minimisation technique provides an excellent model system for studying native enzymes, especially in creating an alternative novel biocatalyst. Miniaturised proteins may have enhanced stability, a crucial characteristic for large-scale production and industrial applications. In this study, a huge enzyme molecule, known as diamine oxidase (DAO, comprising 700 amino acids), was selected to undergo the process. By retaining the arrangement of the original functional sites of DAO in the fourth domain, a mini DAO can be designed via homology modelling. After several downsizing processes, a final configuration of 220 amino acids displayed high binding affinity towards histamine, a short-chain substrate that was catalysed by the parental DAO. The configuration also showed enhanced affinity towards a long-chain substrate known as spermidine. The gene for the designed protein was cloned and expressed in pET102/TOPO vector and overexpressed in E. coli BL21 (DE3). The new mini DAO had similar temperature tolerance and versatile substrates specificity characteristics as its parental protein. An active mini-protein with these characteristics is potentially useful for several applications such as detecting biogenic amines in the biological fluids and the environment that may give rise to health issues.

High-Throughput doi: 10.3390/ht7030020

Authors: Adam P. Sage Victor D. Martinez Brenda C. Minatel Michelle E. Pewarchuk Erin A. Marshall Gavin M. MacAulay Roland Hubaux Dustin D. Pearson Aaron A. Goodarzi Graham Dellaire Wan L. Lam

Malignant mesothelioma is an aggressive and lethal asbestos-related disease. Diagnosis of malignant mesothelioma is particularly challenging and is further complicated by the lack of disease subtype-specific markers. As a result, it is especially difficult to distinguish malignant mesothelioma from benign reactive mesothelial proliferations or reactive fibrosis. Additionally, mesothelioma diagnoses can be confounded by other anatomically related tumors that can invade the pleural or peritoneal cavities, collectively resulting in delayed diagnoses and greatly affecting patient management. High-throughput analyses have uncovered key genomic and epigenomic alterations driving malignant mesothelioma. These molecular features have the potential to better our understanding of malignant mesothelioma biology as well as to improve disease diagnosis and patient prognosis. Genomic approaches have been instrumental in identifying molecular events frequently occurring in mesothelioma. As such, we review the discoveries made using high-throughput technologies, including novel insights obtained from the analysis of the non-coding transcriptome, and the clinical potential of these genetic and epigenetic findings in mesothelioma. Furthermore, we aim to highlight the potential of these technologies in the future clinical applications of the novel molecular features in malignant mesothelioma.

High-Throughput doi: 10.3390/ht7030019

Authors: David Wilson Norelle L. Daly

Venomics is the integration of proteomic, genomic and transcriptomic approaches to study venoms. Advances in these approaches have enabled increasingly more comprehensive analyses of venoms to be carried out, overcoming to some extent the limitations imposed by the complexity of the venoms and the small quantities that are often available. Advances in bioinformatics and high-throughput functional assay screening approaches have also had a significant impact on venomics. A combination of all these techniques is critical for enhancing our knowledge on the complexity of venoms and their potential therapeutic and agricultural applications. Here we highlight recent advances in these fields and their impact on venom analyses.

High-Throughput doi: 10.3390/ht7020018

Authors: Clément Regnault Dharmendra S. Dheeman Axel Hochstetter

In this review, we give an overview of the current state of microfluidic-based high-throughput drug assays. In this highly interdisciplinary research field, various approaches have been applied to high-throughput drug screening, including microtiter plate, droplets microfluidics as well as continuous flow, diffusion and concentration gradients-based microfluidic drug assays. Therefore, we reviewed over 100 recent publications in the field and sorted them according to their microfluidic approach. As a result, we are showcasing, comparing and discussing broadly applied approaches as well as singular promising ones that might contribute to shaping the future of this field.

High-Throughput doi: 10.3390/ht7020017

Authors: Giuseppe Agapito Pietro Hiram Guzzi Mario Cannataro

Personalized medicine is an aspect of the P4 medicine (predictive, preventive, personalized and participatory) based precisely on the customization of all medical characters of each subject. In personalized medicine, the development of medical treatments and drugs is tailored to the individual characteristics and needs of each subject, according to the study of diseases at different scales from genotype to phenotype scale. To make concrete the goal of personalized medicine, it is necessary to employ high-throughput methodologies such as Next Generation Sequencing (NGS), Genome-Wide Association Studies (GWAS), Mass Spectrometry or Microarrays, that are able to investigate a single disease from a broader perspective. A side effect of high-throughput methodologies is the massive amount of data produced for each single experiment, that poses several challenges (e.g., high execution time and required memory) to bioinformatic software. Thus a main requirement of modern bioinformatic softwares, is the use of good software engineering methods and efficient programming techniques, able to face those challenges, that include the use of parallel programming and efficient and compact data structures. This paper presents the design and the experimentation of a comprehensive software pipeline, named microPipe, for the preprocessing, annotation and analysis of microarray-based Single Nucleotide Polymorphism (SNP) genotyping data. A use case in pharmacogenomics is presented. The main advantages of using microPipe are: the reduction of errors that may happen when trying to make data compatible among different tools; the possibility to analyze in parallel huge datasets; the easy annotation and integration of data. microPipe is available under Creative Commons license, and is freely downloadable for academic and not-for-profit institutions.

High-Throughput doi: 10.3390/ht7020016

Authors: Jessica Roberts Aoife Power Shaneel Chandra James Chapman Daniel Cozzolino

The current knowledge of the main factors governing livestock, crop and plant quality as well as yield in different species is incomplete. For example, this can be evidenced by the persistence of benchmark crop varieties for many decades in spite of the gains achieved over the same period. In recent years, it has been demonstrated that molecular breeding based on DNA markers has led to advances in breeding (animal and crops). However, these advances are not in the way that it was anticipated initially by the researcher in the field. According to several scientists, one of the main reasons for this was related to the evidence that complex target traits such as grain yield, composition or nutritional quality depend on multiple factors in addition to genetics. Therefore, some questions need to be asked: are the current approaches in molecular genetics the most appropriate to deal with complex traits such as yield or quality? Are the current tools for phenotyping complex traits enough to differentiate among genotypes? Do we need to change the way that data is collected and analysed?

High-Throughput doi: 10.3390/ht7020015

Authors: Martina Lardi Gabriella Pessi

Biological nitrogen fixation gives legumes a pronounced growth advantage in nitrogen-deprived soils and is of considerable ecological and economic interest. In exchange for reduced atmospheric nitrogen, typically given to the plant in the form of amides or ureides, the legume provides nitrogen-fixing rhizobia with nutrients and highly specialised root structures called nodules. To elucidate the molecular basis underlying physiological adaptations on a genome-wide scale, functional genomics approaches, such as transcriptomics, proteomics, and metabolomics, have been used. This review presents an overview of the different functional genomics approaches that have been performed on rhizobial symbiosis, with a focus on studies investigating the molecular mechanisms used by the bacterial partner to interact with the legume. While rhizobia belonging to the alpha-proteobacterial group (alpha-rhizobia) have been well studied, few studies to date have investigated this process in beta-proteobacteria (beta-rhizobia).

High-Throughput doi: 10.3390/ht7020014

Authors: Destiny Anyaiwe Gautam Singh George Wilson Timothy Geddes

Alzheimer’s disease is rapidly becoming an endemic for people over the age of 65. A vital path towards reversing this ominous trend is the building of reliable diagnostic devices for definite and early diagnoses in lieu of the longitudinal, usually inconclusive and non-generalize-able methods currently in use. In this article, we present a survey of methods for mining pools of mass spectrometer saliva data in relation to diagnosing Alzheimer’s disease. The computational methods provides new approaches for appropriately gleaning latent information from mass spectra data. They improve traditional machine learning algorithms and are most fit for handling matrix data points including solving problems beyond protein identifications and biomarker discovery.

High-Throughput doi: 10.3390/ht7020013

Authors: Ann-Kristin Becker Holger Erfle Manuel Gunkel Nina Beil Lars Kaderali Vytaute Starkuviene

Multi-well plates and cell arrays enable microscopy-based screening assays in which many samples can be analysed in parallel. Each of the formats possesses its own strengths and weaknesses, but reference comparisons between these platforms and their application rationale is lacking. We aim to fill this gap by comparing two RNA interference (RNAi)-mediated fluorescence microscopy-based assays, namely epidermal growth factor (EGF) internalization and cell cycle progression, on both platforms. Quantitative analysis revealed that both platforms enabled the generation of data with the appearance of the expected phenotypes significantly distinct from the negative controls. The measurements of cell cycle progression were less variable in multi-well plates. The result can largely be attributed to higher cell numbers resulting in less data variability when dealing with the assay generating phenotypic cell subpopulations. The EGF internalization assay with a uniform phenotype over nearly the whole cell population performed better on cell arrays than in multi-well plates. The result was achieved by scoring five times less cells on cell arrays than in multi-well plates, indicating the efficiency of the cell array format. Our data indicate that the choice of the screening platform primarily depends on the type of the cellular assay to achieve a maximum data quality and screen efficiency.

High-Throughput doi: 10.3390/ht7020012

Authors: Vehary Sakanyan

Exogenous reactive chemicals can impair cellular homeostasis and are often associated with the development of cancer. Significant progress has been achieved by studying the macromolecular interactions of chemicals that possess various electron-withdrawing groups and the elucidation of the protective responses of cells to chemical interventions. However, the formation of electrophilic species inside the cell and the relationship between oxydative and electrophilic stress remain largely unclear. Derivatives of nitro-benzoxadiazole (also referred as nitro-benzofurazan) are potent producers of hydrogen peroxide and have been used as a model to study the generation of reactive species in cancer cells. This survey highlights the pivotal role of Cu/Zn superoxide dismutase 1 (SOD1) in the production of reactive oxygen and electrophilic species in cells exposed to cell-permeable chemicals. Lipophilic electrophiles rapidly bind to SOD1 and induce stable and functionally active dimers, which produce excess hydrogen peroxide leading to aberrant cell signalling. Moreover, reactive oxygen species and reactive electrophilic species, simultaneously generated by redox reactions, behave as independent entities that attack a variety of proteins. It is postulated that the binding of the electrophilic moiety to multiple proteins leading to impairing different cellular functions may explain unpredictable side effects in patients undergoing chemotherapy with reactive oxygen species (ROS)-inducing drugs. The identification of proteins susceptible to electrophiles at early steps of oxidative and electrophilic stress is a promising way to offer rational strategies for dealing with stress-related malignant tumors.

High-Throughput doi: 10.3390/ht7020011

Authors: Taban Eslami Fahad Saeed

Functional magnetic resonance imaging (fMRI) is a non-invasive brain imaging technique, which has been regularly used for studying brain’s functional activities in the past few years. A very well-used measure for capturing functional associations in brain is Pearson’s correlation coefficient. Pearson’s correlation is widely used for constructing functional network and studying dynamic functional connectivity of the brain. These are useful measures for understanding the effects of brain disorders on connectivities among brain regions. The fMRI scanners produce huge number of voxels and using traditional central processing unit (CPU)-based techniques for computing pairwise correlations is very time consuming especially when large number of subjects are being studied. In this paper, we propose a graphics processing unit (GPU)-based algorithm called Fast-GPU-PCC for computing pairwise Pearson’s correlation coefficient. Based on the symmetric property of Pearson’s correlation, this approach returns N ( N − 1 ) / 2 correlation coefficients located at strictly upper triangle part of the correlation matrix. Storing correlations in a one-dimensional array with the order as proposed in this paper is useful for further usage. Our experiments on real and synthetic fMRI data for different number of voxels and varying length of time series show that the proposed approach outperformed state of the art GPU-based techniques as well as the sequential CPU-based versions. We show that Fast-GPU-PCC runs 62 times faster than CPU-based version and about 2 to 3 times faster than two other state of the art GPU-based methods.

High-Throughput doi: 10.3390/ht7020010

Authors: Maxime Huet Myriam Cubizolles Arnaud Buhot

Pre-transfusion bedside compatibility test is mandatory to check that the donor and the recipient present compatible groups before any transfusion is performed. Although blood typing devices are present on the market, they still suffer from various drawbacks, like results that are based on naked-eye observation or difficulties in blood handling and process automation. In this study, we addressed the development of a red blood cells (RBC) agglutination assay for point-of-care blood typing. An injection molded microfluidic chip that is designed to enhance capillary flow contained anti-A or anti-B dried reagents inside its microchannel. The only blood handling step in the assay protocol consisted in the deposit of a blood drop at the tip of the biochip, and imaging was then achieved. The embedded reagents were able to trigger RBC agglutination in situ, allowing for us to monitor in real time the whole process. An image processing algorithm was developed on diluted bloods to compute real-time agglutination indicator and was further validated on undiluted blood. Through this proof of concept, we achieved efficient, automated, real time, and quantitative measurement of agglutination inside a passive biochip for blood typing which could be further generalized to blood biomarker detection and quantification.

High-Throughput doi: 10.3390/ht7020009

Authors: Kerem Bingol

Metabolomics has made significant progress in multiple fronts in the last 18 months. This minireview aimed to give an overview of these advancements in the light of their contribution to targeted and untargeted metabolomics. New computational approaches have emerged to overcome the manual absolute quantitation step of metabolites in one-dimensional (1D) 1H nuclear magnetic resonance (NMR) spectra. This provides more consistency between inter-laboratory comparisons. Integration of two-dimensional (2D) NMR metabolomics databases under a unified web server allowed for very accurate identification of the metabolites that have been catalogued in these databases. For the remaining uncatalogued and unknown metabolites, new cheminformatics approaches have been developed by combining NMR and mass spectrometry (MS). These hybrid MS/NMR approaches accelerated the identification of unknowns in untargeted studies, and now they are allowing for profiling ever larger number of metabolites in application studies.

High-Throughput doi: 10.3390/ht7010008

Authors: Valeria D’Argenio

Recent and rapid technological advances in molecular sciences have dramatically increased the ability to carry out high-throughput studies characterized by big data production. This, in turn, led to the consequent negative effect of highlighting the presence of a gap between data yield and their analysis. Indeed, big data management is becoming an increasingly important aspect of many fields of molecular research including the study of human diseases. Now, the challenge is to identify, within the huge amount of data obtained, that which is of clinical relevance. In this context, issues related to data interpretation, sharing and storage need to be assessed and standardized. Once this is achieved, the integration of data from different -omic approaches will improve the diagnosis, monitoring and therapy of diseases by allowing the identification of novel, potentially actionably biomarkers in view of personalized medicine.

High-Throughput doi: 10.3390/ht7010007

Authors: Marta-Marina Pérez-Alonso Víctor Carrasco-Loba Joaquín Medina Jesús Vicente-Carbajosa Stephan Pollmann

Over the last three decades, novel “omics” platform technologies for the sequencing of DNA and complementary DNA (cDNA) (RNA-Seq), as well as for the analysis of proteins and metabolites by mass spectrometry, have become more and more available and increasingly found their way into general laboratory life. With this, the ability to generate highly multivariate datasets on the biological systems of choice has increased tremendously. However, the processing and, perhaps even more importantly, the integration of “omics” datasets still remains a bottleneck, although considerable computational and algorithmic advances have been made in recent years. In this mini-review, we use a number of recent “multi-omics” approaches realized in our laboratories as a common theme to discuss possible pitfalls of applying “omics” approaches and to highlight some useful tools for data integration and visualization in the form of an exemplified case study. In the selected example, we used a combination of transcriptomics and metabolomics alongside phenotypic analyses to functionally characterize a small number of Cycling Dof Transcription Factors (CDFs). It has to be remarked that, even though this approach is broadly used, the given workflow is only one of plenty possible ways to characterize target proteins.

High-Throughput doi: 10.3390/ht7010006

Authors: Guofeng Meng

The progress of cancer genome sequencing projects yields unprecedented information of mutations for numerous patients. However, the complexity of mutation profiles of cancer patients hinders the further understanding to mechanisms of oncogenesis. One basic question is how to find mutations with functional impacts. In this work, we introduce a computational method to predict functional somatic mutations of each patient by integrating mutation recurrence with expression profile similarity. With this method, the functional mutations are determined by checking the mutation enrichment among a group of patients with similar expression profiles. We applied this method to three cancer types and identified the functional mutations. Comparison of the predictions for three cancer types suggested that most of the functional mutations were cancer-type-specific with one exception to p53. By checking predicted results, we found that our method effectively filtered non-functional mutations resulting from large protein sizes. In addition, this method can also perform functional annotation to each patient to describe their association with signalling pathways or biological processes. In breast cancer, we predicted “cell adhesion” and other terms to be significantly associated with oncogenesis.

High-Throughput doi: 10.3390/ht7010005

Authors: Anton G. Kutikhin Maxim Yu. Sinitsky Arseniy E. Yuzhalin Elena A. Velikanova

Among applicable high-throughput techniques in cardiovascular biology, whole-transcriptome sequencing is of particular use. By utilizing RNA that is isolated from virtually all cells and tissues, the entire transcriptome can be evaluated. In comparison with other high-throughput approaches, RNA sequencing is characterized by a relatively low-cost and large data output, which permits a comprehensive analysis of spatiotemporal variation in the gene expression profile. Both shear stress and cyclic strain exert hemodynamic force upon the arterial endothelium and are considered to be crucial determinants of endothelial physiology. Laminar blood flow results in a high shear stress that promotes atheroresistant endothelial phenotype, while a turbulent, oscillatory flow yields a pathologically low shear stress that disturbs endothelial homeostasis, making respective arterial segments prone to atherosclerosis. Severe atherosclerosis significantly impairs blood supply to the organs and frequently requires bypass surgery or an arterial replacement surgery that requires tissue-engineered vascular grafts. To provide insight into patterns of gene expression in endothelial cells in native or bioartificial arteries under different biomechanical conditions, this article discusses applications of whole-transcriptome sequencing in endothelial mechanobiology and vascular tissue engineering.

High-Throughput doi: 10.3390/ht7010004

Authors: Anuradha Roy

Drug discovery encompasses processes ranging from target selection and validation to the selection of a development candidate. While comprehensive drug discovery work flows are implemented predominantly in the big pharma domain, early discovery focus in academia serves to identify probe molecules that can serve as tools to study targets or pathways. Despite differences in the ultimate goals of the private and academic sectors, the same basic principles define the best practices in early discovery research. A successful early discovery program is built on strong target definition and validation using a diverse set of biochemical and cell-based assays with functional relevance to the biological system being studied. The chemicals identified as hits undergo extensive scaffold optimization and are characterized for their target specificity and off-target effects in in vitro and in animal models. While the active compounds from screening campaigns pass through highly stringent chemical and Absorption, Distribution, Metabolism, and Excretion (ADME) filters for lead identification, the probe discovery involves limited medicinal chemistry optimization. The goal of probe discovery is identification of a compound with sub-µM activity and reasonable selectivity in the context of the target being studied. The compounds identified from probe discovery can also serve as starting scaffolds for lead optimization studies.

High-Throughput doi: 10.3390/ht7010003

Authors: High-Throughput Editorial Office

Peer review is an essential part in the publication process, ensuring that High-Throughput maintains high quality standards for its published papers [...]

High-Throughput doi: 10.3390/ht7010002

Authors: Maddalena Cagnone Anna Bardoni Paolo Iadarola Simona Viglio

Very often the clinical features of rare neurodegenerative disorders overlap with those of other, more common clinical disturbances. As a consequence, not only the true incidence of these disorders is underestimated, but many patients also experience a significant delay before a definitive diagnosis. Under this scenario, it appears clear that any accurate tool producing information about the pathological mechanisms of these disorders would offer a novel context for their precise identification by strongly enhancing the interpretation of symptoms. With the advent of proteomics, detection and identification of proteins in different organs/tissues, aimed at understanding whether they represent an attractive tool for monitoring alterations in these districts, has become an area of increasing interest. The aim of this report is to provide an overview of the most recent applications of proteomics as a new strategy for identifying biomarkers with a clinical utility for the investigation of rare neurodegenerative disorders.

High-Throughput doi: 10.3390/ht7010001

Authors: Laura Smith Callahan

Although a number of combinatorial/high-throughput approaches have been developed for biomaterial hydrogel optimization, a gradient sample approach is particularly well suited to identify hydrogel property thresholds that alter cellular behavior in response to interacting with the hydrogel due to reduced variation in material preparation and the ability to screen biological response over a range instead of discrete samples each containing only one condition. This review highlights recent work on cell–hydrogel interactions using a gradient material sample approach. Fabrication strategies for composition, material and mechanical property, and bioactive signaling gradient hydrogels that can be used to examine cell–hydrogel interactions will be discussed. The effects of gradients in hydrogel samples on cellular adhesion, migration, proliferation, and differentiation will then be examined, providing an assessment of the current state of the field and the potential of wider use of the gradient sample approach to accelerate our understanding of matrices on cellular behavior.

High-Throughput doi: 10.3390/ht6040018

Authors: Viviana Carcamo Yañez Jens Göpfert Markus Otto Hayrettin Tumani Andreas Peter Thomas Joos

Procalcitonin (PCT) is well established as a highly specific biomarker for the detection of bacterial infections and sepsis. However, the currently available diagnostic tests are not able to detect very low or very early increases of PCT or even baseline levels in healthy individuals or patients with non-bacterial infections. In order to be able to detect these very low concentrations of PCT, a sandwich immunoassay was developed using high sensitivity Single Molecule Array technology (Simoa). The assay was thoroughly validated and applied to analyze human cerebrospinal fluid (CSF) and serum samples from patients with bacterial or viral meningitis as well as CSF, serum, and K2 EDTA plasma from healthy control subjects. A 50-fold increase in sensitivity compared to the current gold standard assays was achieved, which was sensitive enough for the detection of baseline PCT levels. Both serum and CSF showed significantly elevated PCT levels in patients with bacterial meningitis compared to patients with viral meningitis and the healthy control group. Procalcitonin concentration levels for patients with viral meningitis and the control group could be measured, but were not significantly different. The determination of PCT in the low pg·mL−1 range could help to improve the monitoring of bacterial infectious diseases, as PCT level changes could be detected earlier.

High-Throughput doi: 10.3390/ht6040017

Authors: Prabhodh Abbineni Jens Coorssen

Abstract: Regulated exocytosis enables a range of physiological functions including neurotransmission, and the late steps (i.e., docking, priming and Ca2+-triggered membrane fusion) are modulated by a highly conserved set of proteins and lipids. Many of the molecular components and biochemical interactions required have been identified; the precise mechanistic steps they modulate and the biochemical interactions that need to occur across steps are still the subject of intense investigation. Particularly, although the involvement of phosphorylation in modulating exocytosis has been intensively investigated over the past three decades, it is unclear which phosphorylation events are a conserved part of the fundamental fusion mechanism and/or serve as part of the physiological fusion machine (e.g., to modulate Ca2+ sensitivity). Here, the homotypic fusion of cortical vesicles was monitored by utilizing new high-throughput, cost-effective assays to assess the influence of 17 small molecule phospho-modulators on docking/priming, Ca2+ sensitivity and membrane fusion. Specific phosphatases and casein kinase 2 are implicated in modulating the Ca2+ sensitivity of fusion, whereas sphingosine kinase is implicated in modulating the ability of vesicles to fuse. These results indicate the presence of multiple kinases and phosphatases on the vesicles and critical phosphorylation sites on vesicle membrane proteins and lipids that directly influence late steps of regulated exocytosis.

High-Throughput doi: 10.3390/ht6040016

Authors: Sjors In ’t Veld Kim Duong Mireille Snel Anke Witteveen Inès Beumer Leonie Delahaye Diederik Wehkamp René Bernards Annuska Glas Sun Tian

Colorectal cancer patients with the BRAF(p.V600E) mutation have poor prognosis in metastatic setting. Personalized treatment options and companion diagnostics are needed to better treat these patients. Previously, we developed a 58-gene signature to characterize the distinct gene expression pattern of BRAF-mutation-like subtype (accuracy 91.1%). Further experiments repurposed drug Vinorelbine as specifically lethal to this BRAF-mutation-like subtype. The aim of this study is to translate this 58-gene signature from a research setting to a robust companion diagnostic that can use formalin-fixed, paraffin-embedded (FFPE) samples to select patients with the BRAF-mutation-like subtype. BRAF mutation and gene expression data of 302 FFPE samples were measured (mutants = 57, wild-type = 245). The performance of the 58-gene signature in FFPE samples showed a high sensitivity of 89.5%. In the identified BRAF-mutation-like subtype group, 50% of tumours were known BRAF mutants, and 50% were BRAF wild-type. The stability of the 58-gene signature in FFPE samples was evaluated by two control samples over 40 independent experiments. The standard deviations (SD) were within the predefined criteria (control 1: SD = 0.091, SD/Range = 3.0%; control 2: SD = 0.169, SD/Range = 5.5%). The fresh frozen version and translated FFPE version of this 58-gene signature were compared using 170 paired fresh frozen and FFPE samples and the result showed high consistency (agreement = 99.3%). In conclusion, we translated this 58-gene signature to a robust companion diagnostic that can use FFPE samples.

High-Throughput doi: 10.3390/ht6040015

Authors: Angela Filomena Jens C. Göpfert Darragh Duffy Stanislas Pol Mohamed Abdel-Hamid Gamal Esmat Arnaud Fontanet Matthew Albert Thomas Joos Nicole Schneiderhan-Marra

Hepatitis C is one of the leading causes of hepatocellular carcinoma and remains at a high prevalence in Egypt and other resource-limited countries. Several hepatitis C virus (HCV) genotypes are distributed throughout the world, with genotype 4 being most common in North and Central Africa. We developed a multiplex serological assay for the detection of the HCV specific humoral immune response, with a focus on genotype 4. For the multiplex HCV assay we used twelve antigenic regions of different HCV proteins (core, and non-structural (NS) proteins NS3, NS4, NS5A, NS5B) and validated the assay technically and clinically. In comparison to a commercially available test, our assay revealed a higher sensitivity for genotype 4, and is therefore more suited for studying immune seroconversion in samples from acutely infected Egyptian HCV patients. Furthermore, our assay discriminates acutely and chronically infected HCV patients. Of 296 well characterized HCV patient samples, 83.9% of the acute samples and 86.5% of the chronic samples could be correctly classified. In sum, this newly developed serological HCV assay has a higher sensitivity for HCV genotype 4, and can thus improve diagnostic accuracy. Through the discrimination of acutely and chronically infected HCV patients the assay may be useful in supporting clinical management of HCV patients.

High-Throughput doi: 10.3390/ht6040014

Authors: Angela Filomena Frank Pessler Manas Akmatov Gérard Krause Darragh Duffy Barbara Gärtner Markus Gerhard Matthew Albert Thomas Joos Nicole Schneiderhan-Marra

The spread of infectious diseases and vaccination history are common subjects of epidemiological and immunological research studies. Multiplexed serological assays are useful tools for assessing both current and previous infections as well as vaccination efficacy. We developed a serological multi-pathogen assay for hepatitis A, B and C virus, cytomegalovirus (CMV), Toxoplasma gondii, and Helicobacter pylori using a bead-based multiplex assay format. The multi-pathogen assay consisting of 15 antigens was utilized for the analysis of the serological response in elderly individuals of an influenza vaccination study (n = 34). The technical assay validation revealed a mean intra-assay precision of coefficient of variation (CV) = 3.2 ± 1.5% and a mean inter-assay precision of CV = 8.2 ± 5.3% across all 15 antigens and all tested samples, indicating a robust test system. Furthermore, the assay shows high sensitivities (ranging between 94% and 100%) and specificities (ranging between 93% and 100%) for the different pathogens. The highest seroprevalence rates in our cohort were observed for hepatitis A virus (HAV; 73.5%), followed by CMV (70.6%), T. gondii (67.6%) and H. pylori (32.4%). Seroprevalences for hepatitis B virus (HBV, 8.8%) and hepatitis C virus (HCV, 0%) were low. The seroprevalences observed in our study were similar to those from other population-based studies in Germany. In summary, we conclude that our multiplex serological assay represents a suitable tool for epidemiological studies.

High-Throughput doi: 10.3390/ht6040013

Authors: Stefania Bortoluzzi Federica Lovisa Enrico Gaffo Lara Mussolin

Extracellular vesicles (EVs) secreted from many cell types play important roles in intercellular communication, both as paracrine and endocrine factors, as they can circulate in biological fluids, including plasma. Amid EVs, exosomes are actively secreted vesicles that contain proteins, lipids, soluble factors, and nucleic acids, including microRNAs (miRNAs) and other classes of small RNAs (sRNA). miRNAs are prominent post‐transcriptional regulators of gene expression and epigenetic silencers of transcription. We concisely review the roles of miRNAs in cell‐fate determination and development and their regulatory activity on almost all the processes and pathways controlling tumor formation and progression. Next, we consider the evidence linking exosomes to tumor progression, particularly to the setting‐up of permissive pre‐metastatic niches. The study of exosomes in patients with different survival and therapy response can inform on the possible correlations between exosomal cargo and disease features. Moreover, the exploration of circulating exosomes as possible sources of non‐invasive biomarkers could give new implements for anti‐cancer therapy and metastasis prevention. Since the characterization of sRNAs in exosomes of cancer patients sparks opportunities to better understand their roles in cancer, we briefly present current experimental and computational protocols for sRNAs analysis in circulating exosomes by RNA‐seq.

High-Throughput doi: 10.3390/ht6030012

Authors: Shizuka Uchida

Increasing evidence suggests that the numbers of long non‐coding RNAs (lncRNAs) are more than those of protein‐coding genes in various organisms. Although the detection methods for lncRNAs are being increasingly established, there are advantages and disadvantages that exist for each method. In this opinion article, I highlight the differences between microarrays and RNA sequencing (RNA‐seq) for the detection of lncRNAs. Compared to RNA‐seq, microarrays are limited to the known sequences. However, the detection method as well as data analysis workflow is more established, which makes it easier to analyze the data for bench scientists without extensive knowledge about computer programming. In order to highlight the usage of microarrays over RNA‐seq for the detection of lncRNAs, we are organizing a special issue for High‐Throughput called “Microarrays in Non‐Coding RNAs Profiling”, which will include the specific usages of microarrays for lncRNAs.

High-Throughput doi: 10.3390/ht6030011

Authors: Elisheva Friedman Negin Alizadeh Zvi Loewy

This study aims to consider the microbial distribution in oral disease, as well as gene analysis and expression, in elucidating: 1, the fundamental underpinnings of oral disease, and 2, the potential relationship between oral diseases and systemic health. A key focus is identifying the microbiota associated with oral disease manifestations characterized by both conventional microbiological and molecular methods. Variations in the observed microbial populations characterized by conventional and molecular approaches have been identified for caries, periodontitis, peri-implantitis, and stomatitis. The discovery of therapeutic approaches for oral disease will require comprehensive microbial and genomic analysis. This study evaluated the current state of the relevant microbial and genomic information for several prevalent oral diseases.

High-Throughput doi: 10.3390/ht6030010

Authors: Massimo Negrini

MDPI’s journal Microarrays released its first volume in 2012. Since then, the journal has published 129 articles on the topic of microarrays, including their applications, analysis and new developments. [...]