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Biology
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New Resources and Methods for Reconstructing Human-Pathogen Co-evolution
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New Resources and Methods for Reconstructing Human-Pathogen Co-evolution

A special issue of Biology (ISSN 2079-7737). This special issue belongs to the section "Evolutionary Biology".

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 12052

Special Issue Editors

Dr. Ville Pimenoff

E-Mail Website
Guest Editor
Department of Laboratory Medicine, Div. of Pathology, Karolinska Institutet, 141 86 Stockholm, Sweden
Interests: computational metagenomics; exposome; virome; microbiome; cancer; vaccines; Bayesian Inference
Dr. Riaan F. Rifkin

E-Mail Website
Guest Editor
Oppenheimer Endowed Fellow in Molecular Archaeology, Department of Biochemistry, Genetics and Microbiology, Centre for Microbial Ecology and Genomics (CMEG), University of Pretoria, Hatfield 0002, South Africa
Interests: human evolution; ethnography; anthropology; ancient DNA; palaeo-epidemiology; microbiome
Dr. Simon Underdown

E-Mail Website
Guest Editor
Human Origins and Palaeoenvironments Research Group, Oxford Brookes University, Oxford OX3 0BP, UK
Interests: human evolution; ancient DNA; human-pathogen coevolution; disease exchange

Special Issue Information

Dear Colleagues,

Every human in history has suffered from some form of infectious disease. Today, we are amassing enormous amounts of molecular data from humans and their infectious agents through recently developed wearable devices that collect microbial exposure data, as well as high-throughput sequencing and proteomics methods. Moreover, advanced molecular methods have enabled the retrieval of pathogen and host molecular material from a wide range of archaeological contexts, including human remains. Concurrently, new mathematical modelling, deep learning and “big data” computational methods are developing to manage, analyse and interpret larger and more complex datasets. The combination of these new datasets and cutting-edge analytical techniques allows us to better approximate the complex patterns of human–pathogen interactions that have shaped our health and wellbeing for millennia. Reconstructing pathogen–human parallel histories in this way will reveal the likely origins and long-term effects of contemporary human pathogens; these in-depth findings may also have clinical relevance in predicting future disease outcomes and emerging pathogen epidemics.

This Special Issue will take a multidisciplinary approach geared towards utilising the currently available clinical and historical human infectious agent data to systematically explore the molecular histories of human infectious diseases. The aim of this Special Issue is to bring clinicians, evolutionary biologists, archaeologists and data scientists together to provide readers with an up-to-date and state-of-the-art summary of sampling resources, electronic data archiving and sharing and computational and statistical methods, to provide a comprehensive analysis of human pathogen exposure and the molecular histories of human infectious diseases. Research articles, review articles as well as short communications are invited. We ask you to send us an abstract prior to submission to ensure that your work fits within the scope of this Special Issue.

 

Dr. Ville Pimenoff
Dr. Riaan F. Rifkin
Dr. Simon Underdown
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biology is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Dr. Ville Pimenoff
Dr. Riaan F. Rifkin
Dr. Simon Underdown
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biology is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • infectious diseases
  • open data
  • archaeological archives
  • bio-banking
  • systems biology
  • molecular histories
  • human-pathogen co-evolution
  • pathogen exposure

Published Papers (3 papers)

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Research

21 pages, 3854 KiB  
Article
Genomic Analysis of 18th-Century Kazakh Individuals and Their Oral Microbiome
by Anna E. White, Toni de-Dios, Pablo Carrión, Gian Luca Bonora, Laia Llovera, Elisabetta Cilli, Esther Lizano, Maral K. Khabdulina, Daniyar T. Tleugabulov, Iñigo Olalde, Tomàs Marquès-Bonet, François Balloux, Davide Pettener, Lucy van Dorp, Donata Luiselli and Carles Lalueza-Fox
Biology 2021, 10(12), 1324; https://doi.org/10.3390/biology10121324 - 14 Dec 2021
Cited by 1 | Viewed by 5224
Abstract
The Asian Central Steppe, consisting of current-day Kazakhstan and Russia, has acted as a highway for major migrations throughout history. Therefore, describing the genetic composition of past populations in Central Asia holds value to understanding human mobility in this pivotal region. In this [...] Read more.
The Asian Central Steppe, consisting of current-day Kazakhstan and Russia, has acted as a highway for major migrations throughout history. Therefore, describing the genetic composition of past populations in Central Asia holds value to understanding human mobility in this pivotal region. In this study, we analyse paleogenomic data generated from five humans from Kuygenzhar, Kazakhstan. These individuals date to the early to mid-18th century, shortly after the Kazakh Khanate was founded, a union of nomadic tribes of Mongol Golden Horde and Turkic origins. Genomic analysis identifies that these individuals are admixed with varying proportions of East Asian ancestry, indicating a recent admixture event from East Asia. The high amounts of DNA from the anaerobic Gram-negative bacteria Tannerella forsythia, a periodontal pathogen, recovered from their teeth suggest they may have suffered from periodontitis disease. Genomic analysis of this bacterium identified recently evolved virulence and glycosylation genes including the presence of antibiotic resistance genes predating the antibiotic era. This study provides an integrated analysis of individuals with a diet mostly based on meat (mainly horse and lamb), milk, and dairy products and their oral microbiome. Full article
(This article belongs to the Special Issue New Resources and Methods for Reconstructing Human-Pathogen Co-evolution)
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12 pages, 4344 KiB  
Article
Phylogeography and Re-Evaluation of Evolutionary Rate of Powassan Virus Using Complete Genome Data
by Artem N. Bondaryuk, Tatiana E. Peretolchina, Elena V. Romanova, Anzhelika V. Yudinceva, Evgeny I. Andaev and Yurij S. Bukin
Biology 2021, 10(12), 1282; https://doi.org/10.3390/biology10121282 - 06 Dec 2021
Cited by 5 | Viewed by 2510
Abstract
In this paper, we revealed the genetic structure and migration history of the Powassan virus (POWV) reconstructed based on 25 complete genomes available in NCBI and ViPR databases (accessed in June 2021). The usage of this data set allowed us to perform a [...] Read more.
In this paper, we revealed the genetic structure and migration history of the Powassan virus (POWV) reconstructed based on 25 complete genomes available in NCBI and ViPR databases (accessed in June 2021). The usage of this data set allowed us to perform a more precise assessment of the evolutionary rate of this virus. In addition, we proposed a simple Bayesian technique for the evaluation and visualization of ‘temporal signal dynamics’ along the phylogenetic tree. We showed that the evolutionary rate value of POWV is 3.3 × 10−5 nucleotide substitution per site per year (95% HPD, 2.0 × 10−5–4.7 × 10−5), which is lower than values reported in the previous studies. Divergence of the most recent common ancestor (MRCA) of POWV into two independent genetic lineages most likely occurred in the period between 2600 and 6030 years ago. We assume that the divergence of the virus lineages happened due to the melting of glaciers about 12,000 years ago, which led to the disappearance of the Bering Land Bridge between Eurasia and North America (the modern Alaskan territory) and spatial division of the viral areal into two parts. Genomic data provide evidence of the virus migrations between two continents. The mean migration rate detected from the Far East of Russia to North America was one event per 1750 years. The migration to the opposite direction occurred approximately once per 475 years. Full article
(This article belongs to the Special Issue New Resources and Methods for Reconstructing Human-Pathogen Co-evolution)
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15 pages, 2709 KiB  
Article
An Alignment-Independent Approach for the Study of Viral Sequence Diversity at Any Given Rank of Taxonomy Lineage
by Li Chuin Chong, Wei Lun Lim, Kenneth Hon Kim Ban and Asif M. Khan
Biology 2021, 10(9), 853; https://doi.org/10.3390/biology10090853 - 31 Aug 2021
Viewed by 3550
Abstract
The study of viral diversity is imperative in understanding sequence change and its implications for intervention strategies. The widely used alignment-dependent approaches to study viral diversity are limited in their utility as sequence dissimilarity increases, particularly when expanded to the genus or higher [...] Read more.
The study of viral diversity is imperative in understanding sequence change and its implications for intervention strategies. The widely used alignment-dependent approaches to study viral diversity are limited in their utility as sequence dissimilarity increases, particularly when expanded to the genus or higher ranks of viral species lineage. Herein, we present an alignment-independent algorithm, implemented as a tool, UNIQmin, to determine the effective viral sequence diversity at any rank of the viral taxonomy lineage. This is done by performing an exhaustive search to generate the minimal set of sequences for a given viral non-redundant sequence dataset. The minimal set is comprised of the smallest possible number of unique sequences required to capture the diversity inherent in the complete set of overlapping k-mers encoded by all the unique sequences in the given dataset. Such dataset compression is possible through the removal of unique sequences, whose entire repertoire of overlapping k-mers can be represented by other sequences, thus rendering them redundant to the collective pool of sequence diversity. A significant reduction, namely ~44%, ~45%, and ~53%, was observed for all reported unique sequences of species Dengue virus, genus Flavivirus, and family Flaviviridae, respectively, while still capturing the entire repertoire of nonamer (9-mer) viral peptidome diversity present in the initial input dataset. The algorithm is scalable for big data as it was applied to ~2.2 million non-redundant sequences of all reported viruses. UNIQmin is open source and publicly available on GitHub. The concept of a minimal set is generic and, thus, potentially applicable to other pathogenic microorganisms of non-viral origin, such as bacteria. Full article
(This article belongs to the Special Issue New Resources and Methods for Reconstructing Human-Pathogen Co-evolution)
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