Real-time identification of epistatic interactions in SARS-CoV-2 from large genome collections.

BACKGROUND: The emergence of the SARS-CoV-2 virus has highlighted the importance of genomic epidemiology in understanding the evolution of pathogens and guiding public health interventions. The Omicron variant in particular has underscored the role of epistasis in the evolution of lineages with both higher infectivity and immune escape, and therefore the necessity to update surveillance pipelines to detect them early on. RESULTS: In this study, we apply a method based on mutual information between positions in a multiple sequence alignment, which is capable of scaling up to millions of samples. We show how it can reliably predict known experimentally validated epistatic interactions, even when using as little as 10,000 sequences, which opens the possibility of making it a near real-time prediction system. We test this possibility by modifying the method to account for the sample collection date and apply it retrospectively to multiple sequence alignments for each month between March 2020 and March 2023. We detected a cornerstone epistatic interaction in the Spike protein between codons 498 and 501 as soon as seven samples with a double mutation were present in the dataset, thus demonstrating the method's sensitivity. We test the ability of the method to make inferences about emerging interactions by testing candidates predicted after March 2023, which we validate experimentally. CONCLUSIONS: We show how known epistatic interaction in SARS-CoV-2 can be detected with high sensitivity, and how emerging ones can be quickly prioritized for experimental validation, an approach that could be implemented downstream of pandemic genome sequencing efforts.

Systemic antibody responses against gut microbiota flagellins implicate shared and divergent immune reactivity in Crohn's disease and chronic fatigue syndrome.

BACKGROUND: Elevated systemic antibody responses against gut microbiota flagellins are observed in both Crohn's disease (CD) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), suggesting potential serological biomarkers for diagnosis. However, flagellin-specific antibody repertoires and functional roles in the diseases remain incompletely understood. Bacterial flagellins can be categorized into three types depending on their interaction with toll-like receptor 5 (TLR5): (1) "stimulator" and (2) "silent" flagellins, which bind TLR5 through a conserved N-terminal motif, with only stimulators activating TLR5 (involving a C-terminal domain); (3) "evader" flagellins of pathogens, which entirely circumvent TLR5 activation via mutations in the N-terminal TLR5 binding motif. RESULTS: Here, we show that both CD and ME/CFS patients exhibit elevated antibody responses against distinct regions of flagellins compared to healthy individuals. N-terminal binding to Lachnospiraceae flagellins was comparable in both diseases, while C-terminal binding was more prevalent in CD. N-terminal antibody-bound flagellin sequences were similar across CD and ME/CFS, resembling "stimulator" and "silent" flagellins more than evaders. However, C-terminal antibody-bound flagellins showed a higher resemblance to the stimulator than to silent flagellins in CD, which was not observed in ME/CFS. CONCLUSIONS: These findings suggest that antibody binding to the N-terminal domain of stimulator and silent flagellins may impact TLR5 activation in both CD and ME/CFS patients. Blocking this interaction could lead commensal bacteria to be recognized as pathogenic evaders, potentially contributing to dysregulation in both diseases. Furthermore, elevated antibody binding to the C-terminal domain of stimulator flagellins in CD may explain pathophysiological differences between the diseases. Overall, these results highlight the diagnostic potential of these antibody responses and lay a foundation for deeper mechanistic studies of flagellin/TLR5 interactions and their impact on innate/adaptive immunity balance.

Independent origins and evolution of the secondary replicons of the class Gammaproteobacteria.

Multipartite genomes, consisting of more than one replicon, have been found in approximately 10 % of bacteria, many of which belong to the phylum Proteobacteria. Many aspects of their origin and evolution, and the possible advantages related to this type of genome structure, remain to be elucidated. Here, we performed a systematic analysis of the presence and distribution of multipartite genomes in the class Gammaproteobacteria, which includes several genera with diverse lifestyles. Within this class, multipartite genomes are mainly found in the order Alteromonadales (mostly in the genus Pseudoalteromonas) and in the family Vibrionaceae. Our data suggest that the emergence of secondary replicons in Gammaproteobacteria is rare and that they derive from plasmids. Despite their multiple origins, we highlighted the presence of evolutionary trends such as the inverse proportionality of the genome to chromosome size ratio, which appears to be a general feature of bacteria with multipartite genomes irrespective of taxonomic group. We also highlighted some functional trends. The core gene set of the secondary replicons is extremely small, probably limited to essential genes or genes that favour their maintenance in the genome, while the other genes are less conserved. This hypothesis agrees with the idea that the primary advantage of secondary replicons could be to facilitate gene acquisition through horizontal gene transfer, resulting in replicons enriched in genes associated with adaptation to different ecological niches. Indeed, secondary replicons are enriched both in genes that could promote adaptation to harsh environments, such as those involved in antibiotic, biocide and metal resistance, and in functional categories related to the exploitation of environmental resources (e.g. carbohydrates), which can complement chromosomal functions.

Dental calculus microbiome correlates with dietary intake.

BACKGROUND: Dental calculus is the result of dental plaque mineralization, originating from the tooth-associated bacterial biofilm. Recent evidence revealed that the dental calculus microbiome has a more complex composition than previously considered, including an unstructured mix of both aerobes and anaerobes bacteria. Actually, we lack information about the influence of host lifestyle factors, such as diet and health on this highly biodiverse ecosystem. Here, we provide a pilot study investigating dental calculus microbial biodiversity and its relation with the host diet. METHODS: We collected 40 dental calculus samples during routine dental inspection; deoxyribonucleic acid was extracted and analyzed through 16S amplicon sequencing, while dietary information was retrieved through a questionnaire. Associations between diet and oral bacteria taxonomy and functional pathways were statistically tested. RESULTS: Overall, microbiome composition was dominated by 10 phyla and 39 bacterial genera, which were differently distributed among samples. Cluster analysis revealed four main groups based on the taxonomic profile and two groups based on functional pathways. Each taxonomic cluster was dominated by different microbial biomarkers: Streptococcus, Rothia, Tannerella, Lautropia, and Fusobacterium. Bacteria genera and pathways were also associated with specific dietary elements, especially vegetable and fruit intake suggesting an overall effect of diet on dental calculus microbiome. CONCLUSIONS: The present study demonstrates that there exists an inter-variability in the microbial composition of dental calculus among individuals of a rather homogeneous population. Furthermore, the observed biodiversity and microbial functions can find an association with specific dietary habits, such as a high-fiber diet or a protein-rich diet.

Ancient oral microbiomes support gradual Neolithic dietary shifts towards agriculture.

The human microbiome has recently become a valuable source of information about host life and health. To date little is known about how it may have evolved during key phases along our history, such as the Neolithic transition towards agriculture. Here, we shed light on the evolution experienced by the oral microbiome during this transition, comparing Palaeolithic hunter-gatherers with Neolithic and Copper Age farmers that populated a same restricted area in Italy. We integrate the analysis of 76 dental calculus oral microbiomes with the dietary information derived from the identification of embedded plant remains. We detect a stronger deviation from the hunter-gatherer microbiome composition in the last part of the Neolithic, while to a lesser extent in the early phases of the transition. Our findings demonstrate that the introduction of agriculture affected host microbiome, supporting the hypothesis of a gradual transition within the investigated populations.

Fast, Ungapped Reads Mapping Using Squid.

Advances in Next Generation Sequencing technologies allow us to inspect and unlock the genome to a level of detail that was unimaginable only a few decades ago. Omics-based studies are casting a light on the patterns and determinants of disease conditions in populations, as well as on the influence of microbial communities on human health, just to name a few. Through increasing volumes of sequencing information, for example, it is possible to compare genomic features and analyze the modulation of the transcriptome under different environmental stimuli. Although protocols for NGS preparation are intended to leave little to no space for contamination of any kind, a noticeable fraction of sequencing reads still may not uniquely represent what was intended to be sequenced in the first place. If a natural consequence of a sequencing sample is to assess the presence of features of interest by mapping the obtained reads to a genome of reference, sometimes it is useful to determine the fraction of those that do not map, or that map discordantly, and store this information to a new file for subsequent analyses. Here we propose a new mapper, which we called Squid, that among other accessory functionalities finds and returns sequencing reads that match or do not match to a reference sequence database in any orientation. We encourage the use of Squid prior to any quantification pipeline to assess, for instance, the presence of contaminants, especially in RNA-Seq experiments.