The gastrointestinal tract is abundantly colonized by microbes, yet the translocation of oral species to the intestine is considered a rare aberrant event, and a hallmark of disease. By studying salivary and fecal microbial strain populations of 310 species in 470 individuals from five countries, we found that transmission to, and subsequent colonization of, the large intestine by oral microbes is common and extensive among healthy individuals. We found evidence for a vast majority of oral species to be transferable, with increased levels of transmission in colorectal cancer and rheumatoid arthritis patients and, more generally, for species described as opportunistic pathogens. This establishes the oral cavity as an endogenous reservoir for gut microbial strains, and oral-fecal transmission as an important process that shapes the gastrointestinal microbiome in health and disease.

Background: Recent evidence has linked the gut microbiome to host behavior via the gut-brain axis [1-3]; however, the underlying mechanisms remain unexplored. Here, we determined the links between host genetics, the gut microbiome and memory using the genetically defined Collaborative Cross (CC) mouse cohort, complemented with microbiome and metabolomic analyses in conventional and germ-free (GF) mice. Results: A genome-wide association analysis (GWAS) identified 715 of 76,080 single-nucleotide polymorphisms (SNPs) that were significantly associated with short-term memory using the passive avoidance model. The identified SNPs were enriched in genes known to be involved in learning and memory functions. By 16S rRNA gene sequencing of the gut microbial community in the same CC cohort, we identified specific microorganisms that were significantly correlated with longer latencies in our retention test, including a positive correlation with Lactobacillus. Inoculation of GF mice with individual species of Lactobacillus (L. reuteri F275, L. plantarum BDGP2 or L. brevis BDGP6) resulted in significantly improved memory compared to uninoculated or E. coli DH10B inoculated controls. Untargeted metabolomics analysis revealed significantly higher levels of several metabolites, including lactate, in the stools of Lactobacillus-colonized mice, when compared to GF control mice. Moreover, we demonstrate that dietary lactate treatment alone boosted memory in conventional mice. Mechanistically, we show that both inoculation with Lactobacillus or lactate treatment significantly increased the levels of the neurotransmitter, gamma-aminobutyric acid (GABA), in the hippocampus of the mice. Conclusion: Together, this study provides new evidence for a link between Lactobacillus and memory and our results open possible new avenues for treating memory impairment disorders using specific gut microbial inoculants and/or metabolites.

Miscanthus sp. biomass could satisfy future biorefinery value chains. However, its use is largely untapped due to high recalcitrance. The termite and its gut microbiome are considered the most efficient lignocellulose degrading system in nature. Here, we investigate at holobiont level the dynamic adaptation of Cortaritermes sp. to imposed Miscanthus diet, with a long-term objective of overcoming lignocellulose recalcitrance. We use an integrative omics approach combined with enzymatic characterisation of carbohydrate active enzymes from termite gut Fibrobacteres and Spirochaetae. Modified gene expression profiles of gut bacteria suggest a shift towards utilisation of cellulose and arabinoxylan, two main components of Miscanthus lignocellulose. Low identity of reconstructed microbial genomes to closely related species supports the hypothesis of a strong phylogenetic relationship between host and its gut microbiome. This study provides a framework for better understanding the complex lignocellulose degradation by the higher termite gut system and paves a road towards its future bioprospecting.

The development of reliable, mixed-culture biotechnological processes hinges on understanding how microbial ecosystems respond to disturbances. Here we reveal extensive phenotypic plasticity and niche complementarity in oleaginous microbial populations from a biological wastewater treatment plant. We perform meta-omics analyses (metagenomics, metatranscriptomics, metaproteomics and metabolomics) on in situ samples over 14 months at weekly intervals. Based on 1,364 de novo metagenome-assembled genomes, we uncover four distinct fundamental niche types. Throughout the time-series, we observe a major, transient shift in community structure, coinciding with substrate availability changes. Functional omics data reveals extensive variation in gene expression and substrate usage amongst community members. Ex situ bioreactor experiments confirm that responses occur within five hours of a pulse disturbance, demonstrating rapid adaptation by specific populations. Our results show that community resistance and resilience are a function of phenotypic plasticity and niche complementarity, and set the foundation for future ecological engineering efforts.

HighlightsDeep learning has become widely used in different fields of computer science such as face recognition, but also in biology, for example to detect malignant skin cancers based on images.Deep learning applied to microscopy images of biofilm colonization patterns accurately characterized its bacterial composition.Deep learning applications only rarely outperform human experts in classification tasks. Here however, deep learning reached an accuracy of 90%, therefore clearly outperforming human experts (50% accurate).Our method provides an accurate alternative to standard, time-consuming biochemical methods, using visual information only.

Introduction Long COVID is characterized by a variety of symptoms and an important burden for affected people. Our objective was to describe Long COVID symptomatology according to initial COVID-19 severity. Methods Predi-COVID cohort study participants, recruited at the time of acute COVID-19 infection, completed a detailed 12-month symptoms and quality of life questionnaire. Frequencies and co-occurrences of symptoms were assessed. Results Among the 289 participants who fully completed the 12-month questionnaire, 59.5% reported at least one symptom with a median of 6 symptoms. Participants with an initial moderate or severe acute illness declared more frequently one or more symptoms (82.6% vs 38.6%, p < 0.001) and had on average 6.8 more symptoms (CI 95% [4.18; 9.38]) than initially asymptomatic participants who developed symptoms after the acute infection. Overall, 12.5% of the participants could not envisage coping with their symptoms in the long term. Frequently reported symptoms, like neurological and cardiovascular symptoms, but also less frequent such as gastrointestinal symptoms, tended to cluster. Conclusion Frequencies and burden of symptoms present 12 months after acute COVID-19 infection increased with the severity of the acute illness. Long COVID likely consists of multiple sub-categories rather than one single entity. This work will contribute to the better understanding of Long COVID and to the definition of precision health strategies.

Highlights d Modeling of combinatorial effects of pre-and probiotic (synbiotic) regimens on cancer d HuMiX represents diet-microbiome-human interactions d The synbiotic regimen reduces molecular hallmarks of cancer d Cocktail of synbiotic-derived small molecules limits cancer self-renewal capacity

Glacier-fed streams (GFSs) exhibit near-freezing temperatures, variable flows, and often high turbidities. Currently, the rapid shrinkage of mountain glaciers is altering the delivery of meltwater, solutes, and particulate matter to GFSs, with unknown consequences for their ecology. Benthic biofilms dominate microbial life in GFSs, and play a major role in their biogeochemical cycling. Mineralization is likely an important process for microbes to meet elemental budgets in these systems due to commonly oligotrophic conditions, and extracellular enzymes retained within the biofilm enable the degradation of organic matter and acquisition of carbon (C), nitrogen (N), and phosphorus (P). The measurement and comparison of these extracellular enzyme activities (EEA) can in turn provide insight into microbial elemental acquisition effort relative to environmental availability. To better understand how benthic biofilm communities meet resource demands, and how this might shift as glaciers vanish under climate change, we investigated biofilm EEA in 20 GFSs varying in glacier influence from New Zealand’s Southern Alps. Using turbidity and distance to the glacier snout normalized for glacier size as proxies for glacier influence, we found that bacterial abundance (BA), chlorophyll a (Chl a), extracellular polymeric substances (EPS), and total EEA per gram of sediment increased with decreasing glacier influence. Yet, when normalized by BA, EPS decreased with decreasing glacier influence, Chl a still increased, and there was no relationship with total EEA. Based on EEA ratios, we found that the majority of GFS microbial communities were N-limited, with a few streams of different underlying bedrock geology exhibiting P-limitation. Cell-specific C-acquiring EEA was positively related to the ratio of Chl a to BA, presumably reflecting the utilization of algal exudates. Meanwhile, cell-specific N-acquiring EEA were positively correlated with the concentration of dissolved inorganic nitrogen (DIN), and both N- and P-acquiring EEA increased with greater cell-specific EPS. Overall, our results reveal greater glacier influence to be negatively related to GFS biofilm biomass parameters, and generally associated with greater microbial N demand. These results help to illuminate the ecology of GFS biofilms, along with their biogeochemical response to a shifting habitat template with ongoing climate change.