Microbiome and Long COVID-19: Current Evidence and Insights
Abstract
1. Introduction
2. Gut Microbiome Alterations in Various Phases of Long COVID
2.1. Altered Gut Microbiome During COVID-19 Infection
2.2. Lasting Changes in Microbial Disruption in Long COVID
2.3. Trends in Taxonomic Shifts in Gut Microbiota
2.4. Oral and Respiratory Microbiomes
2.5. Unique Microbial Clusters Associated with Long COVID Symptoms
2.6. Methodological and Clinical Heterogeneity in COVID-19 Microbiome Studies
3. Proposed Mechanisms Linking Microbiome to Long COVID
3.1. Gut–Immune Axis and Inflammation
3.2. ACE2 and Gut Barrier Dysfunction
3.3. Microbiota-Gut–Brain Axis
3.4. Viral Persistence, Immune Priming and Autoantibody Formation
3.5. The Oral–Lung Aspiration Axis
3.6. Experimental Evidence: Causal Role of Microbiota
4. Microbial Biomarkers of Long COVID
4.1. Reduced SCFA Producers
4.2. Enriched Pathobionts
4.3. Microbiome Diversity Index
4.4. Specific Species or Functions
4.5. Combined Microbiome Signatures
5. Microbiome-Targeted Diagnostics and Therapeutics
5.1. Diagnostic Avenues
5.2. Prebiotics and Diet
5.3. Probiotics and Synbiotics
5.4. Microbiota Transplantation
6. Consensus and Controversies
6.1. Consensus Points
6.2. Controversies and Open Questions
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
5-HT | 5-hydroxytryptamine |
5-HTP | 5-hydroxytryptophan |
ACE2 | Angiotensin-converting enzyme 2 |
Ang | Angiotensin |
C-Trp | C-glycosyltrytophan |
CT | Computed tomography |
EGF | Epidermal growth factor |
FEV1 | Forced expiratory volume |
FGF | Fibroblast growth factor |
FMT | Fecal microbiota transplantation |
FOXP3 | Forkhead box P3 |
FVC | Forced vital capacity |
HDAC | Histone deacetylase |
HSP | Heat-shock protein |
IAA | Indole-3-acetic acid |
ILA | Indole-3-lactic acid |
IFN | Interferon |
IDO | Indoleamine 2,3-dioxygenase |
IPA | Indole-3-propionate |
LBP | Lipopolysaccharide binding protein |
LPS | Lipopolysaccharide |
MAIT | Mucosal-associated invariant T |
MDC | Macrophage-derived chemokine |
ME/CFS | Myalgic encephalomyelitis/chronic fatigue syndrome |
MIP-1b | Macrophage inflammatory protein-1 beta |
MPIF-1 | Myeloid progenitor inhibitory factor 1 |
NF-κB | Nuclear factor kappa-light-chain-enhancer of activated B cells |
NLRP3 | NOD-, LRR-, and pyrin domain-containing protein 3 |
PASC | Post-acute sequelae of COVID-19 |
RAAS | Renin–angiotensin–aldosterone system |
ROS | Reactive oxygen species |
SCFA | Short-chain fatty acid |
Th17 | T helper 17 cells |
TLR | Toll-like receptor |
TNF | Tumor necrosis factor |
Treg | Regulatory T cell |
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Year (Ref.) | Sample (Design) | N | Study Country | Time Since Infection (Months) | Sequencing Method | Microbiome Focus | Key Taxa Alterations | Clinical Outcomes | Main Findings | Limitation |
---|---|---|---|---|---|---|---|---|---|---|
2025 Blankestijn et al. [29] | Post-COVID-19 clinic cohort 3–6 months post-infection; fecal metagenomic sequencing with clustering analysis | 79 | Netherlands | 3–6 | Shotgun metagenomics | Gut | ↓ F. prausnitzii, Eubacterium spp.; ↑ R. gnavus, E. coli, Veillonella, Streptococcus | Pulmonary function (FEV1, FVC, DLCO); severity correlation | Patients with dysbiotic microbiota had poorer lung recovery; dysbiosis linked to severe acute COVID-19 history. | Small single-country study; observational; confounders (diet, meds) not fully controlled. |
2024 Su et al. [30] | Multi-cohort machine learning study predicting PACS phenotypes from microbiome data | Several hundred | China (Hong Kong) | 3–6 | Shotgun metagenomics | Gut | Enterotypes: one depleted in butyrate-producers, enriched in R. gnavus, E. coli | PACS symptom clusters (respiratory, neuro, GI) | Gut enterotypes predicted symptom type with ~89% accuracy; microbiome heterogeneity underpins symptom diversity. | Complex model; regional limitation; predictive, not causal. |
2024 Lau et al. [31] | Non-randomized open-label trial: 30 received multi-donor FMT (capsules), 30 received control | 60 | China (Hong Kong) | 9 | Shotgun metagenomics | Gut | ↑ Gemmiger formicilis, ↑ donor-like microbiota composition | Insomnia, fatigue, anxiety, cortisol levels | FMT improved sleep quality and reduced fatigue/anxiety; safe with no serious AEs. | Open-label, moderate N, short follow-up; limited generalizability. |
2023 Lau et al. [32] | RCT: Long COVID patients randomized 1:1 to synbiotic (SIM01) vs. placebo for 6 months | 463 | China (Hong Kong) | 4–10 | Shotgun metagenomics | Gut | ↑ Bifidobacterium adolescentis, SCFA-producers; ↑ diversity | Symptom improvement (fatigue, memory loss, GI issues, well-being) | Synbiotic improved symptoms and microbiome diversity; microbiome correlated with recovery. | Subjective outcomes; single-center; no objective function gains. |
2023 Zhang et al. [13] | Recovered patients 1 year post-hospitalization (84 long COVID, 103 recovered, 32 controls) | 219 | China (Wuhan) | 12 | 16S rRNA sequencing | Gut | ↓ Eubacterium hallii, Subdoligranulum, Ruminococcus, Agathobacter; ↑ Veillonella | Presence of long COVID symptoms at 12 months | Long COVID associated with reduced diversity and SCFA-producing genera; dysbiosis persisted ≥1 year. | Cross-sectional; single region; no diet control; association only. |
2022 Liu et al. [17] | Prospective cohort followed from diagnosis to 6 months; pre-pandemic controls included | 174 | China (Hong Kong) | 6 | Shotgun metagenomics | Gut | ↓ Faecalibacterium, Bifidobacterium; ↑ R. gnavus, B. vulgatus | Persistence of ≥1 symptom at 6 months (fatigue, respiratory, GI, neuro) | Baseline microbiota predicted long COVID; persistent dysbiosis at 6 months in long COVID. | Single-region cohort; no causal inference; did not adjust for acute severity. |
2021 Haran et al. [33] | Adult COVID-19 outpatients; tongue swabs collected during acute illness; followed until symptom resolution (~37% developed long COVID) | 27 | USA | 0–3 | Shotgun metagenomics | Oral | ↑ Prevotella, Veillonella | Symptom duration; presence of long COVID | Oral dysbiosis linked to prolonged inflammation; microbiota resembled chronic fatigue syndrome. | Small sample; no uninfected controls; observational study. |
2020 Zuo et al. [9] | 15 COVID-19 in-patients with varying severity; 15 uninfected controls; 6 pneumonia controls; longitudinal stool sampling during hospitalization | 36 | China (Hong Kong) | 0–1 | Shotgun metagenomics | Gut | ↑ Coprobacillus, C. ramosum, C. hathewayi; ↓ F. prausnitzii | Acute COVID-19 severity; microbiome persistence post-clearance | Gut dysbiosis persisted from admission to discharge; opportunistic pathogens correlated with severity. | Small hospitalized cohort; no follow-up in mild/asymptomatic cases. |
Year (Ref.) | Sample (Design) | Study Subjects | Pathophysiologic Mechanism | Main Findings | Limitations |
---|---|---|---|---|---|
2025 Barichello et al. [76] | Cross-Sectional Study | Humans | Inflammation | Significant increases in MPIF-1, IL-1 and triglycerides in long-COVID19 patients. β-diversity was reduced, including decreased abundance of Akkermansia spp. No differences were observed in α-diversity data | Could not identify species in 16S rRNA analysis Cognitive assessment 3–4 weeks post-COVID-19 may be suboptimal Findings may be specific to study population or methodology Akkermansia depletion not consistently reported in other studies Psychiatric symptom assessment influenced by multifactorial factors |
2025 Rohrhofer et al. [81] | Prospective Observational Study | Humans | Intestinal Barrier Disruption | Significant associations were present between gastrointestinal and neuropsychiatric symptoms in long COVID. In the post-acute phase, patients showed higher LBP/sCD14, lower IL-33 and higher IL-6 levels, indicating a proinflammatory state and intestinal barrier disruption | Low sample size Self-reported data |
2024 Mussabay et al. [80] | Prospective Cohort Study | Humans | Inflammation | Severe COVID19, complicated by pneumonia, increased presence of proinflammatory bacterial species. In their post-acute phase various cytokines and chemokines such as MDC, IL-1b, TNF-α, FGF-2, EGF, IL-1RA, IFN-α, IL-10, sCD40L, IL-8, IL-12p40 and MIP-1b displayed a proinflammatory profile | Relatively small sample size (n = 60) Included patients that had severe COVID19 disease only |
2024 Song et al. [86] | Experimental Study | Murine | ACE2 | ACE2 knockout mice has increase inflammatory bacterial genera including Deferribacteres, Parasutterella, Catenibacterium, Anaerotruncus, with concomitant decreases in SCFA-producing bacteria. Contrarily, ACE2-overexpression enhanced concentrations of SCFA-producing bacteria such as Lactobacillus, Bifidobacterium, Alisipes, etc. | Study was performed in murine models and not in humans |
2024 Yao et al. [102] | Experimental (Shotgun Metagenomic) with a Meta-Analysis | Human | Neurotransmitters Inflammation | Serum levels of tryptophan and IPA were negatively correlated with inflammatory markers such as circulating cytokines, while C-Trp, ILA and IAA were positively correlated with proinflammatory markers in long COVID patients. Metagenomics of microbiota showed reduction in enzymes involved in tryptophan metabolism in hospitalized patients. Microbiota-derived tryptophan metabolites modified TH1 and TH17 associated cytokine responses and reduced innate cell proinflammatory responses to TLR3 and TLR4 | Only hospitalized patients included Confounding factors such as diet, medications, comorbidities and lifestyle were not adjusted for |
2023 Visvabharathy et al. [109] | Observational, Cross-Sectional Study | Humans | Adaptive Immune Response | Patients with neurological symptoms in the post-acute COVID19 phase have elevated CD4 T cell response and reduced CD8 activation. CD8 T cell production of IL-6 heightened severity of neurologic symptoms | Small sample size Unable to control for time of sample collection with respect to date of COVID19 symptom onset |
2022 Blackett et al. [101] | Randomized Control Trial | Human | Neurotransmitter Regulation | Gut microbiome L-tryptophan synthesis was decreased in patients with more severe gastrointestinal symptoms in acute COVID19. Similar biosynthesis pathways of tryptophan biosynthesis were also decreased in those with severe mental health symptoms in the post-acute phase. | Low sample size 5-HT concentrations were obtained postprandially 2 different cohorts were designed for separate studies, with differences in methods for self-reported mental health symptoms |
2021 Haran et al. [33] | Prospective Cohort Study | Humans | Oral Microbiota Inflammation | Patients with prolonged COVID19 symptoms and progression to long COVID had higher abundance of proinflammatory microbiota including Prevotella and Veillonella. The oral microbiome in long COVID patients were similar to those with chronic fatigue syndrome | Sample size |
2020 Gammazza et al. [107] | Bioinformatics Study | Computational | Molecular Mimicry | HSPs, which are considered human molecular chaperones, participate in molecular mimicry following COVID19 infection. Post-translational modifications can cause autoimmune endothelial damage in the post-acute phase | Hypothesis generated study Scanned for exact peptides No tissue confirmation |
Category/Biomarker Type | Representative Studies (Year, Ref.) | Key Microbial Findings/Taxa or Functions | Potential Clinical or Diagnostic Relevance | Mechanistic or Functional Basis | Limitations/Validation Needs |
---|---|---|---|---|---|
Reduced SCFA Producers | Zhang et al., 2023 [13]; Liu et al., 2022 [17]; Zuo et al., 2020 [9]; Yeoh et al., 2021 [8] | ↓ Faecalibacterium, Eubacterium, Subdoligranulum, Anaerostipes, Bifidobacterium spp.; reduced fecal butyrate levels and SCFA synthesis genes. | Low SCFA-producer abundance may signal increased risk of long COVID or delayed recovery; stool SCFA quantification could aid monitoring. | Loss of butyrate-producing bacteria → reduced anti-inflammatory and mucosal healing capacity → chronic inflammation and barrier dysfunction. | Observed in multiple cohorts but not specific to COVID; further validation in prospective studies needed. |
Enriched Pathobionts | Haran et al., 2021 [33]; Liu et al., 2022 [17]; Su et al., 2024 [30] | ↑ Ruminococcus gnavus, Bacteroides vulgatus (gut); ↑ Prevotella, Veillonella (oral); enrichment of proinflammatory Gram-negative species. | High abundance of these taxa correlates with persistent fatigue, GI, and neurological symptoms; may indicate ongoing mucosal inflammation. | Pathobiont overgrowth → LPS release → immune activation via TLR pathways; cytokine production (IL-6, IL-1β, TNF-α). | Requires cross-validation; ratios like R. gnavus, F. prausnitzii may improve specificity. |
Microbiome Diversity Index | Zhang et al., 2023 [13]; Liu et al., 2022 [17]; Yeoh et al., 2021 [8]; Haran et al., 2021 [33] | Reduced alpha diversity (Chao1, Shannon, Simpson indices) in long COVID vs. recovered or control groups. | Alpha diversity metrics may serve as global indicators of gut health and recovery trajectory after COVID-19. | Lower diversity reflects ecosystem instability and loss of protective taxa; correlates with immune dysregulation and persistent symptoms. | Requires standardization; diversity thresholds vary by population and sequencing platform. |
Specific Species or Functional Genes | Liu et al., 2022 [17]; Lau et al., 2023 [32]; Su et al., 2024 [30] | ↑ Clostridium innocuum, Actinomyces naeslundii, R. gnavus; ↓ SCFA-related genes; ↑ genes for LPS and antibiotic resistance pathways. | Specific species and gene profiles may stratify long COVID subtypes (fatigue-dominant vs. neurocognitive). | Functional shift toward proinflammatory and oxidative pathways; depletion of metabolic and barrier-supportive functions. | Functional gene panels are promising but require longitudinal validation and standard bioinformatics pipelines. |
Combined Microbiome Signatures | Haran et al., 2021 [33]; Su et al., 2024 [30]; Liu et al., 2022 [17] | Integrated microbial signatures combining taxa (e.g., Prevotella: Bifidobacterium ratio) and metabolic pathways via machine learning classifiers. | Predictive models could identify high-risk patients early; basis for stool- or saliva-based diagnostic assays. | Multi-omics integration (metagenomics + metabolomics + transcriptomics) enhances specificity for long COVID risk prediction. | Still experimental; reproducibility across populations and sequencing platforms remains unproven. |
Year (Ref.) | Sample (Design) | N | Microbiome-Targeted Therapy | Main Findings | Limitations |
---|---|---|---|---|---|
2025 Suarez-Morena et al. [139] | Cross-Sectional Study | 305 | Mediterranean Diet | Introduction of a Mediterranean diet in patients with Long COVID improved waist circumference and improved metabolic parameters | Sample size was predominately women and may not be generalizable to men Adherence was gathered through questionnaires |
2024 Cuevas-Sierra et al. [140] | Prospective Cohort Study | 188 | Mediterranean Diet | High adherence to the Mediterranean diet improved inflammatory and oxidative markers. Adherence was also correlated with reduction in LDL-cholesterol and glucose levels. These changes were accompanied by lower Oscillobacter concentrations in high adherence groups which was related to oxidative markers. | Relatively small sample size Only some components of the Mediterranean Diet were used (i.e., olive oil) |
2024 Song et al. [142] | Experimental | 19 | Prebiotics (Inulin) | Inulin supplementation improved concentrations of fecal SCFAs and secondary bile acids in the setting of COVID19 | Experiment was performed in murine models Small sample size |
2024 Lau et al. [32] | Double-Blind Placebo-Controlled Trial | 463 | Synbiotics (SIM01) | Six-month supplementation with a Bifidobacterium-based synbiotic significantly improved fatigue, mental fog, and gastrointestinal symptoms in long COVID patients compared to placebo | Difficult to assess based on severity of initial COVID-19 infection |
2024 Ranisavljev et al. [152] | Double-Blind Placebo-Controlled Trial | 26 | Synbiotic | Three-month supplementation of synbiotics and placebo improved fatigue in Long COVID. Synbiotics attenuated post-exercise malaise. Synbiotics increased choline levels within the thalamus | Sample limited to young-to-middle-aged adults Vaccination status, time since infection, and dietary factors not considered Multi-strain synbiotic and placebo may have confounded effects Small sample size; short 3-month follow-up Limited mechanistic biomarker assessment |
2024 Lau et al. [31] | Pilot Study | 30 | Fecal Microbiota Transplant | After 12 weeks, following FMT, the treatment group exhibited decreased symptoms associated with insomnia and anxiety. Serum cortisol levels were also lower. Depletion of microbial species that produce harmful derivatives were observed and microbiota was similar to donors at the study endpoint. | Low sample size |
2024 Jiang et al. [159] | Double-Blind Placebo-Controlled Trial | 40 | Fecal Microbiota Transplant | FMT showed improvements in diarrhea, depression and neuropsychiatric symptoms in COVID-19. Serum AST/ALT ratio was reduced following FMT | Low sample size |
2022 Santinelli et al. [153] | Retrospective Observational Study | 58 | Probiotics | Probiotic supplementation significantly lowered proportion of COVID-19 patients that reported fatigue. Concentrations of serum amino acids were increased and harmful microbiota byproducts were reduced | Lack of randomization |
2022 Thomas et al. [143] | Double-Blind Placebo-Controlled Trial | 147 | Phytochemical and Probiotics | Addition of phytochemical two-fold reduction in fatigue, three-fold reduction in cough, and two-fold improvement in quality-of-life scores, compared to probiotics alone | Non-randomization of the probiotic element within the study |
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Caliman-Sturdza, O.A.; Hamamah, S.; Iatcu, O.C.; Lobiuc, A.; Bosancu, A.; Covasa, M. Microbiome and Long COVID-19: Current Evidence and Insights. Int. J. Mol. Sci. 2025, 26, 10120. https://doi.org/10.3390/ijms262010120
Caliman-Sturdza OA, Hamamah S, Iatcu OC, Lobiuc A, Bosancu A, Covasa M. Microbiome and Long COVID-19: Current Evidence and Insights. International Journal of Molecular Sciences. 2025; 26(20):10120. https://doi.org/10.3390/ijms262010120
Chicago/Turabian StyleCaliman-Sturdza, Olga A., Sevag Hamamah, Oana C. Iatcu, Andrei Lobiuc, Anca Bosancu, and Mihai Covasa. 2025. "Microbiome and Long COVID-19: Current Evidence and Insights" International Journal of Molecular Sciences 26, no. 20: 10120. https://doi.org/10.3390/ijms262010120
APA StyleCaliman-Sturdza, O. A., Hamamah, S., Iatcu, O. C., Lobiuc, A., Bosancu, A., & Covasa, M. (2025). Microbiome and Long COVID-19: Current Evidence and Insights. International Journal of Molecular Sciences, 26(20), 10120. https://doi.org/10.3390/ijms262010120