Large language models improve annotation of prokaryotic viral proteins.

Viral genomes are poorly annotated in metagenomic samples, representing an obstacle to understanding viral diversity and function. Current annotation approaches rely on alignment-based sequence homology methods, which are limited by the paucity of characterized viral proteins and divergence among viral sequences. Here we show that protein language models can capture prokaryotic viral protein function, enabling new portions of viral sequence space to be assigned biologically meaningful labels. When applied to global ocean virome data, our classifier expanded the annotated fraction of viral protein families by 29%. Among previously unannotated sequences, we highlight the identification of an integrase defining a mobile element in marine picocyanobacteria and a capsid protein that anchors globally widespread viral elements. Furthermore, improved high-level functional annotation provides a means to characterize similarities in genomic organization among diverse viral sequences. Protein language models thus enhance remote homology detection of viral proteins, serving as a useful complement to existing approaches.

The Breast Microbiome in Breast Cancer Risk and Progression: A Narrative Review.

A decade ago, studies in human populations first revealed the existence of a unique microbial community in the breast, a tissue historically viewed as sterile, with microbial origins seeded through the nipple and/or translocation from other body sites. Since then, research efforts have been made to characterize the microbiome in healthy and cancerous breast tissues. The purpose of this review is to summarize the current evidence for the association of the breast microbiome with breast cancer risk and progression. Briefly, while many studies have examined the breast microbiome in patients with breast cancer, and compared it with the microbiome of benign breast disease tissue or normal breast tissue, these studies have varied widely in their sample sizes, methods, and quality of evidence. Thus, while several large and rigorous cross-sectional studies have provided key evidence of an altered microbiome in breast tumors compared with normal adjacent and healthy control tissue, there are few consistent patterns of perturbed microbial taxa. In addition, only one large prospective study has provided evidence of a relationship between the breast tumor microbiota and cancer prognosis. Future research studies featuring large, well-characterized cohorts with prospective follow-up for breast cancer incidence, progression, and response to treatment are warranted.

Preparation, analysis and toxicity characterisation of the redox metabolites of the azo food dye tartrazine.

Tartrazine (E102, FD&C Yellow 5) is a vibrant yellow azo dye added to many processed foods. The safety of this ubiquitous chemical has not been fully elucidated, and it has been linked to allergic reactions and ADHD in some individuals. In our study, bacterial species isolated from human stool decolourised tartrazine and, upon exposure to air, a purple compound formed. Tartrazine is known to undergo reduction in the gut to sulfanilic acid and 4-amino-3-carboxy-5-hydroxy-1-(4-sulfophenyl)pyrazole (SCAP). These metabolites and their derivatives are relevant to the toxicology of tartrazine. The toxicity of sulfanilic acid has been studied before, but the oxidative instability of SCAP has previously prevented full characterisation. We have verified the chemical identity of SCAP and confirmed that the purple-coloured oxidation derivative is 4-(3-carboxy-5-hydroxy-1-(4-sulfophenyl)-1H-pyrazol-4-yl)imino-5-oxo-1-(4-sulfophenyl)-4,5-dihydro-1H-pyrazole-3-carboxylic acid (purpurazoic acid, PPA), as proposed by Westöö in 1965. A yellow derivative of SCAP is proposed to be the hydrolysed oxidation product, 4,5-dioxo-1-(4-sulfophenyl)-4,5-dihydro-1H-pyrazole-3-carboxylic acid. SCAP and PPA are moderately toxic to human cells (IC50 89 and 78 µM against HEK-293, respectively), but had no apparent effect on Escherichia coli and Bacillus subtilis bacteria. These results prompt further analyses of the toxicology of tartrazine and its derivatives.

Large language models improve annotation of viral proteins.

Viral sequences are poorly annotated in environmental samples, a major roadblock to understanding how viruses influence microbial community structure. Current annotation approaches rely on alignment-based sequence ho-mology methods, which are limited by available viral sequences and sequence divergence in viral proteins. Here, we show that protein language model representations capture viral protein function beyond the limits of remote sequence homology by targeting two axes of viral sequence annotation: systematic labeling of protein families and function identification for biologic discovery. Protein language model representations capture protein functional properties specific to viruses and expand the annotated fraction of ocean virome viral protein sequences by 37%. Among unannotated viral protein families, we identify a novel DNA editing protein family that defines a new mobile element in marine picocyanobacteria. Protein language models thus significantly enhance remote homology detection of viral proteins and can be utilized to enable new biological discovery across diverse functional categories.

MAT Gain of Activity Mutation in Helicobacter pylori Is Associated with Resistance to MTAN Transition State Analogues.

Helicobacter pylori is found in the gut lining of more than half of the world's population, causes gastric ulcers, and contributes to stomach cancers. Menaquinone synthesis in H. pylori relies on the rare futalosine pathway, where H. pylori 5'-methylthioadenosine nucleosidase (MTAN) is proposed to play an essential role. Transition state analogues of MTAN, including BuT-DADMe-ImmA (BTDIA) and MeT-DADMe-ImmA (MTDIA), exhibit bacteriostatic action against numerous diverse clinical isolates of H. pylori with minimum inhibitory concentrations (MIC's) of <2 ng/mL. Three H. pylori BTDIA-resistant clones were selected under increasing BTDIA pressure. Whole genome sequencing showed no mutations in MTAN. Instead, resistant clones had mutations in metK, methionine adenosyltransferase (MAT), feoA, a regulator of the iron transport system, and flhF, a flagellar synthesis regulator. The mutation in metK causes expression of a MAT with increased catalytic activity, leading to elevated cellular S-adenosylmethionine. Metabolite analysis and the mutations associated with resistance suggest multiple inputs associated with BTDIA resistance. Human gut microbiome exposed to MTDIA revealed no growth inhibition under aerobic or anaerobic conditions. Transition state analogues of H. pylori MTAN have potential as agents for treating H. pylori infection without disruption of the human gut microbiome or inducing resistance in the MTAN target.

Dietary iron restriction protects against vaso-occlusion and organ damage in murine sickle cell disease.

Sickle cell disease (SCD) is an inherited disorder resulting from a ß-globin gene mutation, and SCD patients experience erythrocyte sickling, vaso-occlusive episodes (VOE), and progressive organ damage. Chronic hemolysis, inflammation, and repeated red blood cell transfusions in SCD can disrupt iron homeostasis. Patients who receive multiple blood transfusions develop iron overload, and another subpopulation of SCD patients manifest iron deficiency. To elucidate connections between dietary iron, the microbiome, and SCD pathogenesis, we treated SCD mice with an iron-restricted diet (IRD). IRD treatment reduced iron availability and hemolysis, decreased acute VOE, and ameliorated chronic organ damage in SCD mice. Our results extend previous studies indicating that the gut microbiota regulate disease in SCD mice. IRD alters microbiota load and improves gut integrity, together preventing crosstalk between the gut microbiome and inflammatory factors such as aged neutrophils, dampening VOE, and organ damage. These findings provide strong evidence for the therapeutic potential of manipulating iron homeostasis and the gut microbiome to ameliorate SCD pathophysiology. Many treatments, which are under development, focus on lowering the systemic iron concentration to relieve disease complications, and our data suggest that iron-induced changes in microbiota load and gut integrity are related- and novel-therapeutic targets.

Bacterial hydrogen sulfide drives cryptic redox chemistry in gut microbial communities.

Microbial biochemistry contributes to a dynamic environment in the gut. Yet, how bacterial metabolites such as hydrogen sulfide (H2S) mechanistically alter the gut chemical landscape is poorly understood. Here we show that microbially generated H2S drives the abiotic reduction of azo (R-N = N-R') xenobiotics, which are commonly found in Western food dyes and drugs. This nonenzymatic reduction of azo compounds is demonstrated in Escherichia coli cultures, in human faecal microbial communities and in vivo in male mice. Changing dietary levels of the H2S xenobiotic redox partner Red 40 transiently decreases mouse faecal sulfide levels, demonstrating that a xenobiotic can attenuate sulfide concentration and alleviate H2S accumulation in vivo. Cryptic H2S redox chemistry thus can modulate sulfur homeostasis, alter the chemical landscape in the gut and contribute to azo food dye and drug metabolism. Interactions between chemicals derived from microbial communities may be a key feature shaping metabolism in the gut.

Genomic surveillance of SARS-CoV-2 during the first year of the pandemic in the Bronx enabled clinical and epidemiological inference.

The Bronx was an early epicenter of the COVID-19 pandemic in the USA. We conducted temporal genomic surveillance of 104 SARS-CoV-2 genomes across the Bronx from March October 2020. Although the local structure of SARS-CoV-2 lineages mirrored those of New York City and New York State, temporal sampling revealed a dynamic and changing landscape of SARS-CoV-2 genomic diversity. Mapping the trajectories of mutations, we found that while some became 'endemic' to the Bronx, other, novel mutations rose in prevalence in the late summer/early fall. Geographically resolved genomes enabled us to distinguish between cases of reinfection and persistent infection in two pediatric patients. We propose that limited, targeted, temporal genomic surveillance has clinical and epidemiological utility in managing the ongoing COVID pandemic.

Longitudinally monitored immune biomarkers predict the timing of COVID-19 outcomes.

The clinical outcome of SARS-CoV-2 infection varies widely between individuals. Machine learning models can support decision making in healthcare by assessing fatality risk in patients that do not yet show severe signs of COVID-19. Most predictive models rely on static demographic features and clinical values obtained upon hospitalization. However, time-dependent biomarkers associated with COVID-19 severity, such as antibody titers, can substantially contribute to the development of more accurate outcome models. Here we show that models trained on immune biomarkers, longitudinally monitored throughout hospitalization, predicted mortality and were more accurate than models based on demographic and clinical data upon hospital admission. Our best-performing predictive models were based on the temporal analysis of anti-SARS-CoV-2 Spike IgG titers, white blood cell (WBC), neutrophil and lymphocyte counts. These biomarkers, together with C-reactive protein and blood urea nitrogen levels, were found to correlate with severity of disease and mortality in a time-dependent manner. Shapley additive explanations of our model revealed the higher predictive value of day post-symptom onset (PSO) as hospitalization progresses and showed how immune biomarkers contribute to predict mortality. In sum, we demonstrate that the kinetics of immune biomarkers can inform clinical models to serve as a powerful monitoring tool for predicting fatality risk in hospitalized COVID-19 patients, underscoring the importance of contextualizing clinical parameters according to their time post-symptom onset.

Resolving the structure of phage-bacteria interactions in the context of natural diversity.

Microbial communities are shaped by viral predators. Yet, resolving which viruses (phages) and bacteria are interacting is a major challenge in the context of natural levels of microbial diversity. Thus, fundamental features of how phage-bacteria interactions are structured and evolve in the wild remain poorly resolved. Here we use large-scale isolation of environmental marine Vibrio bacteria and their phages to obtain estimates of strain-level phage predator loads, and use all-by-all host range assays to discover how phage and host genomic diversity shape interactions. We show that lytic interactions in environmental interaction networks (as observed in agar overlay) are sparse-with phage predator loads being low for most bacterial strains, and phages being host-strain-specific. Paradoxically, we also find that although overlap in killing is generally rare between tailed phages, recombination is common. Together, these results suggest that recombination during cryptic co-infections is an important mode of phage evolution in microbial communities. In the development of phages for bioengineering and therapeutics it is important to consider that nucleic acids of introduced phages may spread into local phage populations through recombination, and that the likelihood of transfer is not predictable based on lytic host range.

Genomic surveillance of SARS-CoV-2 during the first year of the pandemic in the Bronx enabled clinical and epidemiological inference.

The Bronx was an early epicenter of the COVID-19 pandemic in the USA. We conducted temporal genomic surveillance of SARS-CoV-2 genomes across the Bronx from March-October 2020. Although the local structure of SARS-CoV-2 lineages mirrored those of New York City and New York State, temporal sampling revealed a dynamic and changing landscape of SARS-CoV-2 genomic diversity. Mapping the trajectories of variants, we found that while some became 'endemic' to the Bronx, other, novel variants rose in prevalence in the late summer/early fall. Geographically resolved genomes enabled us to distinguish between cases of reinfection and persistent infection in two pediatric patients. We propose that limited, targeted, temporal genomic surveillance has clinical and epidemiological utility in managing the ongoing COVID pandemic. One sentence summary: Temporally and geographically resolved sequencing of SARS-CoV-2 genotypes enabled surveillance of novel genotypes, identification of endemic viral variants, and clinical inferences, in the first wave of the COVID-19 pandemic in the Bronx.

Bioaccumulation as a mechanism of microbiome/drug interactions.

Microbes of the human gut can change drug disposition in the human body and gut ecology via 'bioaccumulation', a process in which bacteria take up compounds intracellularly without chemically modifying them or experiencing changes in growth, as described in Klünemann et al. This work expands current understanding of the types of drug-bacterial interactions in the gut environment.

Degradation of host translational machinery drives tRNA acquisition in viruses.

Viruses are traditionally thought to be under selective pressure to maintain compact genomes and thus depend on host cell translational machinery for reproduction. However, some viruses encode abundant tRNA and other translation-related genes, potentially optimizing for codon usage differences between phage and host. Here, we systematically interrogate selective advantages that carrying 18 tRNAs may convey to a T4-like Vibriophage. Host DNA and RNA degrade upon infection, including host tRNAs, which are replaced by those of the phage. These tRNAs are expressed at levels slightly better adapted to phage codon usage, especially that of late genes. The phage is unlikely to randomly acquire as diverse an array of tRNAs as observed (p = 0.0017). Together, our results support that the main driver behind phage tRNA acquisition is pressure to sustain translation as host machinery degrades, a process resulting in a dynamically adapted codon usage strategy during the course of infection.

Endotoxin Acts Synergistically With Clostridioides difficile Toxin B to Increase Interleukin 1ß Production: A Potential Role for the Intestinal Biome in Modifying the Severity of C. difficile Colitis.

BACKGROUND: Inflammation is a crucial driver of host damage in patients with Clostridioides difficile colitis. We examined the potential for the intestinal microbiome to modify inflammation in patients with C. difficile colitis via the effects of gut-derived endotoxin on cytokine production. METHODS: Endotoxin from Escherichia coli and Pseudomonas aeruginosa as well as stool-derived endotoxin were tested for their ability to enhance interleukin 1ß (IL-1ß) and tumor necrosis factor alpha (TNF-α) production by toxin B-stimulated peripheral blood mononuclear cells. Inflammasome and Toll-like receptor 4 (TLR4) blocking studies were done to discern the importance of these pathways, while metagenomic studies were done to characterize predominant organisms from stool samples. RESULTS: Endotoxin significantly enhanced the ability of C. difficile toxin B to promote IL-1ß production but not TNF-α. The magnitude of this effect varied by endotoxin type and was dependent on combined inflammasome and TLR4 activation. Stool-derived endotoxin exhibited a similar synergistic effect on IL-1ß production with less synergy observed for stools that contained a high proportion of γ-proteobacteria. CONCLUSIONS: The ability of endotoxin to enhance IL-1ß production highlights a manner by which the microbiome can modify inflammation and severity of C. difficile disease. This information may be useful in devising new therapies for severe C. difficile colitis.

Bacterial Swarmers Enriched During Intestinal Stress Ameliorate Damage.

BACKGROUND AND AIMS: Bacterial swarming, a collective movement on a surface, has rarely been associated with human pathophysiology. This study aims to define a role for bacterial swarmers in amelioration of intestinal stress. METHODS: We developed a polymicrobial plate agar assay to detect swarming and screened mice and humans with intestinal stress and inflammation. From chemically induced colitis in mice, as well as humans with inflammatory bowel disease, we developed techniques to isolate the dominant swarmers. We developed swarm-deficient but growth and swim-competent mutant bacteria as isogenic controls. We performed bacterial reinoculation studies in mice with colitis, fecal 16S, and meta-transcriptomic analyses, as well as in vitro microbial interaction studies. RESULTS: We show that bacterial swarmers are highly predictive of intestinal stress in mice and humans. We isolated a novel Enterobacter swarming strain, SM3, from mouse feces. SM3 and other known commensal swarmers, in contrast to their mutant strains, abrogated intestinal inflammation in mice. Treatment of colitic mice with SM3, but not its mutants, enriched beneficial fecal anaerobes belonging to the family of Bacteroidales S24-7. We observed SM3 swarming associated pathways in the in vivo fecal meta-transcriptomes. In vitro growth of S24-7 was enriched in presence of SM3 or its mutants; however, because SM3, but not mutants, induced S24-7 in vivo, we concluded that swarming plays an essential role in disseminating SM3 in vivo. CONCLUSIONS: Overall, our work identified a new but counterintuitive paradigm in which intestinal stress allows for the emergence of swarming bacteria; however, these bacteria act to heal intestinal inflammation.

Engineering the Microbiome to Prevent Adverse Events: Challenges and Opportunities.

In the past decade of microbiome research, we have learned about numerous adverse interactions between the microbiome and medical interventions such as drugs, radiation, and surgery. What if we could alter our microbiomes to prevent these events? In this review, we discuss potential routes to mitigate microbiome adverse events, including applications from the emerging field of microbiome engineering. We highlight cases where the microbiome acts directly on a treatment, such as via differential drug metabolism, and cases where a treatment directly harms the microbiome, such as in radiation therapy. Understanding and preventing microbiome adverse events is a difficult challenge that will require a data-driven approach involving causal statistics, multiomics techniques, and a personalized means of mitigating adverse events. We propose research considerations to encourage productive work in preventing microbiome adverse events, and we highlight the many challenges and opportunities that await.

Finding phenazine.

Analysis of genetic information from soil samples provides insights into bacteria that help to protect crops from fungal diseases by producing chemicals called phenazines.

Topological analysis reveals state transitions in human gut and marine bacterial communities.

Microbiome dynamics influence the health and functioning of human physiology and the environment and are driven in part by interactions between large numbers of microbial taxa, making large-scale prediction and modeling a challenge. Here, using topological data analysis, we identify states and dynamical features relevant to macroscopic processes. We show that gut disease processes and marine geochemical events are associated with transitions between community states, defined as topological features of the data density. We find a reproducible two-state succession during recovery from cholera in the gut microbiomes of multiple patients, evidence of dynamic stability in the gut microbiome of a healthy human after experiencing diarrhea during travel, and periodic state transitions in a marine Prochlorococcus community driven by water column cycling. Our approach bridges small-scale fluctuations in microbiome composition and large-scale changes in phenotype without details of underlying mechanisms, and provides an assessment of microbiome stability and its relation to human and environmental health.

The Cancer Microbiome: Distinguishing Direct and Indirect Effects Requires a Systemic View.

The collection of microbes that live in and on the human body - the human microbiome - can impact on cancer initiation, progression, and response to therapy, including cancer immunotherapy. The mechanisms by which microbiomes impact on cancers can yield new diagnostics and treatments, but much remains unknown. The interactions between microbes, diet, host factors, drugs, and cell-cell interactions within the cancer itself likely involve intricate feedbacks, and no single component can explain all the behavior of the system. Understanding the role of host-associated microbial communities in cancer systems will require a multidisciplinary approach combining microbial ecology, immunology, cancer cell biology, and computational biology - a systems biology approach.