Vibrio cholerae O1 experiences mild bottlenecks through the gastrointestinal tract in some but not all cholera patients.

Vibrio cholerae O1 causes the diarrheal disease cholera, and the small intestine is the site of active infection. During cholera, cholera toxin is secreted from V. cholerae and induces a massive fluid influx into the small intestine, which causes vomiting and diarrhea. Typically, V. cholerae genomes are sequenced from bacteria passed in stool, but rarely from vomit, a fluid that may more closely represents the site of active infection. We hypothesized that V. cholerae O1 population bottlenecks along the gastrointestinal tract would result in reduced genetic variation in stool compared to vomit. To test this, we sequenced V. cholerae genomes from 10 cholera patients with paired vomit and stool samples. Genetic diversity was low in both vomit and stool, consistent with a single infecting population rather than coinfection with divergent V. cholerae O1 lineages. The amount of single-nucleotide variation decreased from vomit to stool in four patients, increased in two, and remained unchanged in four. The variation in gene presence/absence decreased between vomit and stool in eight patients and increased in two. Pangenome analysis of assembled short-read sequencing demonstrated that the toxin-coregulated pilus operon more frequently contained deletions in genomes from vomit compared to stool. However, these deletions were not detected by PCR or long-read sequencing, indicating that interpreting gene presence or absence patterns from short-read data alone may be incomplete. Overall, we found that V. cholerae O1 isolated from stool is genetically similar to V. cholerae recovered from the upper intestinal tract. IMPORTANCE: Vibrio cholerae O1, the bacterium that causes cholera, is ingested in contaminated food or water and then colonizes the upper small intestine and is excreted in stool. Shed V. cholerae genomes from stool are usually studied, but V. cholerae isolated from vomit may be more representative of where V. cholerae colonizes in the upper intestinal epithelium. V. cholerae may experience bottlenecks, or large reductions in bacterial population sizes and genetic diversity, as it passes through the gut. Passage through the gut may select for distinct V. cholerae mutants that are adapted for survival and gut colonization. We did not find strong evidence for such adaptive mutations, and instead observed that passage through the gut results in modest reductions in V. cholerae genetic diversity, and only in some patients. These results fill a gap in our understanding of the V. cholerae life cycle, transmission, and evolution.

Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data.

Wastewater-based surveillance (WBS) is an important epidemiological and public health tool for tracking pathogens across the scale of a building, neighbourhood, city, or region. WBS gained widespread adoption globally during the SARS-CoV-2 pandemic for estimating community infection levels by qPCR. Sequencing pathogen genes or genomes from wastewater adds information about pathogen genetic diversity, which can be used to identify viral lineages (including variants of concern) that are circulating in a local population. Capturing the genetic diversity by WBS sequencing is not trivial, as wastewater samples often contain a diverse mixture of viral lineages with real mutations and sequencing errors, which must be deconvoluted computationally from short sequencing reads. In this study we assess nine different computational tools that have recently been developed to address this challenge. We simulated 100 wastewater sequence samples consisting of SARS-CoV-2 BA.1, BA.2, and Delta lineages, in various mixtures, as well as a Delta-Omicron recombinant and a synthetic 'novel' lineage. Most tools performed well in identifying the true lineages present and estimating their relative abundances and were generally robust to variation in sequencing depth and read length. While many tools identified lineages present down to 1 % frequency, results were more reliable above a 5 % threshold. The presence of an unknown synthetic lineage, which represents an unclassified SARS-CoV-2 lineage, increases the error in relative abundance estimates of other lineages, but the magnitude of this effect was small for most tools. The tools also varied in how they labelled novel synthetic lineages and recombinants. While our simulated dataset represents just one of many possible use cases for these methods, we hope it helps users understand potential sources of error or bias in wastewater sequencing analysis and to appreciate the commonalities and differences across methods.

Phage predation, disease severity, and pathogen genetic diversity in cholera patients.

Despite an increasingly detailed picture of the molecular mechanisms of bacteriophage (phage)-bacterial interactions, we lack an understanding of how these interactions evolve and impact disease within patients. In this work, we report a year-long, nationwide study of diarrheal disease patients in Bangladesh. Among cholera patients, we quantified Vibrio cholerae (prey) and its virulent phages (predators) using metagenomics and quantitative polymerase chain reaction while accounting for antibiotic exposure using quantitative mass spectrometry. Virulent phage (ICP1) and antibiotics suppressed V. cholerae to varying degrees and were inversely associated with severe dehydration depending on resistance mechanisms. In the absence of antiphage defenses, predation was "effective," with a high predator:prey ratio that correlated with increased genetic diversity among the prey. In the presence of antiphage defenses, predation was "ineffective," with a lower predator:prey ratio that correlated with increased genetic diversity among the predators. Phage-bacteria coevolution within patients should therefore be considered in the deployment of phage-based therapies and diagnostics.

Snapshot of cyanobacterial toxins in Pakistani freshwater bodies.

Cyanobacteria are known to produce diverse secondary metabolites that are toxic to aquatic ecosystems and human health. However, data about the cyanotoxins occurrence and cyanobacterial diversity in Pakistan's drinking water reservoirs is scarce. In this study, we first investigated the presence of microcystin, saxitoxin, and anatoxin in 12 water bodies using an enzyme-linked immunosorbent assay (ELISA). The observed cyanotoxin values for the risk quotient (RQ) determined by ELISA indicated a potential risk for aquatic life and human health. Based on this result, we made a more in-depth investigation with a subset of water bodies (served as major public water sources) to analyze the cyanotoxins dynamics and identify potential producers. We therefore quantified the distribution of 17 cyanotoxins, including 12 microcystin congeners using a high-performance liquid chromatography-high-resolution tandem mass spectrometry/mass spectrometry (HPLC-HRMS/MS). Our results revealed for the first time the co-occurrence of multiple cyanotoxins and the presence of cylindrospermopsin in an artificial reservoir (Rawal Lake) and a semi-saline lake (Kallar Kahar). We also quantified several microcystin congeners in a river (Panjnad) with MC-LR and MC-RR being the most prevalent and abundant. To identify potential cyanotoxin producers, the composition of the cyanobacterial community was characterized by shotgun metagenomics sequencing. Despite the noticeable presence of cyanotoxins, Cyanobacteria were not abundant. Synechococcus was the most abundant cyanobacterial genus found followed by a small amount of Anabaena, Cyanobium, Microcystis, and Dolichospermum. Moreover, when we looked at the cyanotoxins genes coverage, we never found a complete microcystin mcy operon. To our knowledge, this is the first snapshot sampling of water bodies in Pakistan. Our results would not only help to understand the geographical spread of cyanotoxin in Pakistan but would also help to improve cyanotoxin risk assessment strategies by screening a variety of cyanobacterial toxins and confirming that cyanotoxin quantification is not necessarily related to producer abundance.

Diversity of Vibrio cholerae O1 through the human gastrointestinal tract during cholera.

Vibrio cholerae O1 causes the diarrheal disease cholera, and the small intestine is the site of active infection. During cholera, cholera toxin is secreted from V. cholerae and induces a massive fluid influx into the small intestine, which causes vomiting and diarrhea. Typically, V. cholerae genomes are sequenced from bacteria passed in stool, but rarely from vomit, a fluid that may more closely represents the site of active infection. We hypothesized that the V. cholerae O1 population bottlenecks along the gastrointestinal tract would result in reduced genetic variation in stool compared to vomit. To test this, we sequenced V. cholerae genomes from ten cholera patients with paired vomit and stool samples. Genetic diversity was low in both vomit and stool, consistent with a single infecting population rather than co-infection with divergent V. cholerae O1 lineages. The number of single nucleotide variants decreased between vomit and stool in four patients, increased in two, and remained unchanged in four. The number of genes encoded in the V. cholerae genome decreased between vomit and stool in eight patients and increased in two. Pangenome analysis of assembled short-read sequencing demonstrated that the toxin-coregulated pilus operon more frequently contained deletions in genomes from vomit compared to stool. However, these deletions were not detected by PCR or long-read sequencing, indicating that interpreting gene presence or absence patterns from short-read data alone may be incomplete. Overall, we found that V. cholerae O1 isolated from stool is genetically similar to V. cholerae recovered from the upper intestinal tract.

Pseudogenes act as a neutral reference for detecting selection in prokaryotic pangenomes.

A long-standing question is to what degree genetic drift and selection drive the divergence in rare accessory gene content between closely related bacteria. Rare genes, including singletons, make up a large proportion of pangenomes (all genes in a set of genomes), but it remains unclear how many such genes are adaptive, deleterious or neutral to their host genome. Estimates of species' effective population sizes (Ne) are positively associated with pangenome size and fluidity, which has independently been interpreted as evidence for both neutral and adaptive pangenome models. We hypothesized that pseudogenes, used as a neutral reference, could be used to distinguish these models. We find that most functional categories are depleted for rare pseudogenes when a genome encodes only a single intact copy of a gene family. In contrast, transposons are enriched in pseudogenes, suggesting they are mostly neutral or deleterious to the host genome. Thus, even if individual rare accessory genes vary in their effects on host fitness, we can confidently reject a model of entirely neutral or deleterious rare genes. We also define the ratio of singleton intact genes to singleton pseudogenes (si/sp) within a pangenome, compare this measure across 668 prokaryotic species and detect a signal consistent with the adaptive value of many rare accessory genes. Taken together, our work demonstrates that comparing with pseudogenes can improve inferences of the evolutionary forces driving pangenome variation.

Longitudinal genomic surveillance of multidrug-resistant Escherichia coli carriage in critical care patients.

Colonization with multidrug-resistant Escherichia coli strains causes a substantial health burden in hospitalized patients. We performed a longitudinal genomics study to investigate the colonization of resistant E. coli strains in critically ill patients and to identify evolutionary changes and strain replacement events within patients. Patients were admitted to the intensive care unit and hematology wards at a major hospital in Lebanon. Perianal swabs were collected from participants on admission and during hospitalization, which were screened for extended-spectrum beta-lactamases and carbapenem-resistant Enterobacterales. We performed whole-genome sequencing and analysis on E. coli strains isolated from patients at multiple time points. The E. coli isolates were genetically diverse, with 11 sequence types (STs) identified among 22 isolates sequenced. Five patients were colonized by E. coli sequence type 131 (ST131)-encoding CTX-M-27, an emerging clone not previously observed in clinical samples from Lebanon. Among the eight patients whose resident E. coli strains were tracked over time, five harbored the same E. coli strain with relatively few mutations over the 5 to 10 days of hospitalization. The other three patients were colonized by different E. coli strains over time. Our study provides evidence of strain diversity within patients during their hospitalization. While strains varied in their antimicrobial resistance profiles, the number of resistance genes did not increase over time. We also show that ST131-encoding CTX-M-27, which appears to be emerging as a globally important multidrug-resistant E. coli strain, is also prevalent among critical care patients and deserves further monitoring.IMPORTANCEUnderstanding the evolution of bacteria over time in hospitalized patients is of utmost significance in the field of infectious diseases. While numerous studies have surveyed genetic diversity and resistance mechanisms in nosocomial infections, time series of within-patient dynamics are rare, and high-income countries are over-represented, leaving low- and middle-income countries understudied. Our study aims to bridge these research gaps by conducting a longitudinal survey of critically ill patients in Lebanon. This allowed us to track Escherichia coli evolution and strain replacements within individual patients over extended periods. Through whole-genome sequencing, we found extensive strain diversity, including the first evidence of the emerging E. coli sequence type 131 clone encoding the CTX-M-27 beta-lactamase in a clinical sample from Lebanon, as well as likely strain replacement events during hospitalization.

Phage predation, disease severity and pathogen genetic diversity in cholera patients.

Despite an increasingly detailed picture of the molecular mechanisms of phage-bacterial interactions, we lack an understanding of how these interactions evolve and impact disease within patients. Here we report a year-long, nation-wide study of diarrheal disease patients in Bangladesh. Among cholera patients, we quantified Vibrio cholerae (prey) and its virulent phages (predators) using metagenomics and quantitative PCR, while accounting for antibiotic exposure using quantitative mass spectrometry. Virulent phage (ICP1) and antibiotics suppressed V. cholerae to varying degrees and were inversely associated with severe dehydration depending on resistance mechanisms. In the absence of anti-phage defenses, predation was 'effective,' with a high predator:prey ratio that correlated with increased genetic diversity among the prey. In the presence of anti-phage defenses, predation was 'ineffective,' with a lower predator:prey ratio that correlated with increased genetic diversity among the predators. Phage-bacteria coevolution within patients should therefore be considered in the deployment of phage-based therapies and diagnostics.

Selection for immune evasion in SARS-CoV-2 revealed by high-resolution epitope mapping and sequence analysis.

Here, we exploit a deep serological profiling strategy coupled with an integrated, computational framework for the analysis of SARS-CoV-2 humoral immune responses. Applying a high-density peptide array (HDPA) spanning the entire proteomes of SARS-CoV-2 and endemic human coronaviruses allowed identification of B cell epitopes and relate them to their evolutionary and structural properties. We identify hotspots of pre-existing immunity and identify cross-reactive epitopes that contribute to increasing the overall humoral immune response to SARS-CoV-2. Using a public dataset of over 38,000 viral genomes from the early phase of the pandemic, capturing both inter- and within-host genetic viral diversity, we determined the evolutionary profile of epitopes and the differences across proteins, waves, and SARS-CoV-2 variants. Lastly, we show that mutations in spike and nucleocapsid epitopes are under stronger selection between than within patients, suggesting that most of the selective pressure for immune evasion occurs upon transmission between hosts.

Two step I to II type transitions in layered Weyl semi-metals and their impact on superconductivity.

Novel "quasi two dimensional" typically layered (semi) metals offer a unique opportunity to control the density and even the topology of the electronic matter. Along with doping and gate voltage, a robust tuning is achieved by application of the hydrostatic pressure. In Weyl semi-metals the tilt of the dispersion relation cones, [Formula: see text] increases with pressure, so that one is able to reach type II ([Formula: see text]starting from the more conventional type I Weyl semi-metals [Formula: see text]. The microscopic theory of such a transition is constructed. It is found that upon increasing pressure the I to II transition occurs in two continuous steps. In the first step the cones of opposite chirality coalesce so that the chiral symmetry is restored, while the second transition to the Fermi surface extending throughout the Brillouin zone occurs at higher pressures. Flattening of the band leads to profound changes in Coulomb screening. Superconductivity observed recently in wide range of pressure and chemical composition in Weyl semi-metals of both types. The phonon theory of pairing including the Coulomb repulsion for a layered material is constructed and applied to recent extensive experiments on [Formula: see text].

Single nucleotide variants in Pseudomonas aeruginosa populations from sputum correlate with baseline lung function and predict disease progression in individuals with cystic fibrosis.

The severity and progression of lung disease are highly variable across individuals with cystic fibrosis (CF) and are imperfectly predicted by mutations in the human gene CFTR, lung microbiome variation or other clinical factors. The opportunistic pathogen Pseudomonas aeruginosa (Pa) dominates airway infections in most CF adults. Here we hypothesized that within-host genetic variation of Pa populations would be associated with lung disease severity. To quantify Pa genetic variation within CF sputum samples, we used deep amplicon sequencing (AmpliSeq) of 209 Pa genes previously associated with pathogenesis or adaptation to the CF lung. We trained machine learning models using Pa single nucleotide variants (SNVs), microbiome diversity data and clinical factors to classify lung disease severity at the time of sputum sampling, and to predict lung function decline after 5 years in a cohort of 54 adult CF patients with chronic Pa infection. Models using Pa SNVs alone classified lung disease severity with good sensitivity and specificity (area under the receiver operating characteristic curve: AUROC=0.87). Models were less predictive of lung function decline after 5 years (AUROC=0.74) but still significantly better than random. The addition of clinical data, but not sputum microbiome diversity data, yielded only modest improvements in classifying baseline lung function (AUROC=0.92) and predicting lung function decline (AUROC=0.79), suggesting that Pa AmpliSeq data account for most of the predictive value. Our work provides a proof of principle that Pa genetic variation in sputum tracks lung disease severity, moderately predicts lung function decline and could serve as a disease biomarker among CF patients with chronic Pa infections.

Zooanthroponotic transmission of SARS-CoV-2 and host-specific viral mutations revealed by genome-wide phylogenetic analysis.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a generalist virus, infecting and evolving in numerous mammals, including captive and companion animals, free-ranging wildlife, and humans. Transmission among non-human species poses a risk for the establishment of SARS-CoV-2 reservoirs, makes eradication difficult, and provides the virus with opportunities for new evolutionary trajectories, including the selection of adaptive mutations and the emergence of new variant lineages. Here, we use publicly available viral genome sequences and phylogenetic analysis to systematically investigate the transmission of SARS-CoV-2 between human and non-human species and to identify mutations associated with each species. We found the highest frequency of animal-to-human transmission from mink, compared with lower transmission from other sampled species (cat, dog, and deer). Although inferred transmission events could be limited by sampling biases, our results provide a useful baseline for further studies. Using genome-wide association studies, no single nucleotide variants (SNVs) were significantly associated with cats and dogs, potentially due to small sample sizes. However, we identified three SNVs statistically associated with mink and 26 with deer. Of these SNVs, ~⅔ were plausibly introduced into these animal species from local human populations, while the remaining ~⅓ were more likely derived in animal populations and are thus top candidates for experimental studies of species-specific adaptation. Together, our results highlight the importance of studying animal-associated SARS-CoV-2 mutations to assess their potential impact on human and animal health.

Community diversity is associated with intra-species genetic diversity and gene loss in the human gut microbiome.

How the ecological process of community assembly interacts with intra-species diversity and evolutionary change is a longstanding question. Two contrasting hypotheses have been proposed: Diversity Begets Diversity (DBD), in which taxa tend to become more diverse in already diverse communities, and Ecological Controls (EC), in which higher community diversity impedes diversification. Previously, using 16S rRNA gene amplicon data across a range of microbiomes, we showed a generally positive relationship between taxa diversity and community diversity at higher taxonomic levels, consistent with the predictions of DBD (Madi et al., 2020). However, this positive 'diversity slope' plateaus at high levels of community diversity. Here we show that this general pattern holds at much finer genetic resolution, by analyzing intra-species strain and nucleotide variation in static and temporally sampled metagenomes from the human gut microbiome. Consistent with DBD, both intra-species polymorphism and strain number were positively correlated with community Shannon diversity. Shannon diversity is also predictive of increases in polymorphism over time scales up to ~4-6 months, after which the diversity slope flattens and becomes negative - consistent with DBD eventually giving way to EC. Finally, we show that higher community diversity predicts gene loss at a future time point. This observation is broadly consistent with the Black Queen Hypothesis, which posits that genes with functions provided by the community are less likely to be retained in a focal species' genome. Together, our results show that a mixture of DBD, EC, and Black Queen may operate simultaneously in the human gut microbiome, adding to a growing body of evidence that these eco-evolutionary processes are key drivers of biodiversity and ecosystem function.

Efficient computation of contributional diversity metrics from microbiome data with FuncDiv.

MOTIVATION: Microbiome datasets with taxa linked to the functions (e.g. genes) they encode are becoming more common as metagenomics sequencing approaches improve. However, these data are challenging to analyze due to their complexity. Summary metrics, such as the alpha and beta diversity of taxa contributing to each function (i.e. contributional diversity), represent one approach to investigate these data, but currently there are no straightforward methods for doing so. RESULTS: We addressed this gap by developing FuncDiv, which efficiently performs these computations. Contributional diversity metrics can provide novel insights that would be impossible to identify without jointly considering taxa and functions. AVAILABILITY AND IMPLEMENTATION: FuncDiv is distributed under a GNU Affero General Public License v3.0 and is available at https://github.com/gavinmdouglas/FuncDiv. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Impact of Stagnation on the Diversity of Cyanobacteria in Drinking Water Treatment Plant Sludge.

Health-related concerns about cyanobacteria-laden sludge of drinking water treatment plants (DWTPs) have been raised in the past few years. Microscopic taxonomy, shotgun metagenomic sequencing, and microcystin (MC) measurement were applied to study the fate of cyanobacteria and cyanotoxins after controlled sludge storage (stagnation) in the dark in a full-scale drinking water treatment plant within 7 to 38 days. For four out of eight dates, cyanobacterial cell growth was observed by total taxonomic cell counts during sludge stagnation. The highest observed cell growth was 96% after 16 days of stagnation. Cell growth was dominated by potential MC producers such as Microcystis, Aphanocapsa, Chroococcus, and Dolichospermum. Shotgun metagenomic sequencing unveiled that stagnation stress shifts the cyanobacterial communities from the stress-sensitive Nostocales (e.g., Dolichospermum) order towards less compromised orders and potential MC producers such as Chroococcales (e.g., Microcystis) and Synechococcales (e.g., Synechococcus). The relative increase of cyanotoxin producers presents a health challenge when the supernatant of the stored sludge is recycled to the head of the DWTP or discharged into the source. These findings emphasize the importance of a strategy to manage cyanobacteria-laden sludge and suggest practical approaches should be adopted to control health/environmental impacts of cyanobacteria and cyanotoxins in sludge.

Shotgun Metagenomic Sequencing to Assess Cyanobacterial Community Composition following Coagulation of Cyanobacterial Blooms.

The excessive proliferation of cyanobacteria in surface waters is a widespread problem worldwide, leading to the contamination of drinking water sources. Short- and long-term solutions for managing cyanobacterial blooms are needed for drinking water supplies. The goal of this research was to investigate the cyanobacteria community composition using shotgun metagenomics in a short term, in situ mesocosm experiment of two lakes following their coagulation with ferric sulfate (Fe2(SO4)3) as an option for source water treatment. Among the nutrient paramenters, dissolved nitrogen was related to Microcystis in both Missisquoi Bay and Petit Lac St. François, while the presence of Synechococcus was related to total nitrogen, dissolved nitrogen, dissolved organic carbon, and dissolved phosphorus. Results from the shotgun metagenomic sequencing showed that Dolichospermum and Microcystis were the dominant genera in all of the mesocosms in the beginning of the sampling period in Missisquoi Bay and Petit Lac St. François, respectively. Potentially toxigenic genera such as Microcystis were correlated with intracellular microcystin concentrations. A principal component analysis showed that there was a change of the cyanobacterial composition at the genus level in the mesocosms after two days, which varied across the studied sites and sampling time. The cyanobacterial community richness and diversity did not change significantly after its coagulation by Fe2(SO4)3 in all of the mesocosms at either site. The use of Fe2(SO4)3 for an onsite source water treatment should consider its impact on cyanobacterial community structure and the reduction of toxin concentrations.

Comprehensive Phylogenomics of Methylobacterium Reveals Four Evolutionary Distinct Groups and Underappreciated Phyllosphere Diversity.

Methylobacterium is a group of methylotrophic microbes associated with soil, fresh water, and particularly the phyllosphere, the aerial part of plants that has been well studied in terms of physiology but whose evolutionary history and taxonomy are unclear. Recent work has suggested that Methylobacterium is much more diverse than thought previously, questioning its status as an ecologically and phylogenetically coherent taxonomic genus. However, taxonomic and evolutionary studies of Methylobacterium have mostly been restricted to model species, often isolated from habitats other than the phyllosphere and have yet to utilize comprehensive phylogenomic methods to examine gene trees, gene content, or synteny. By analyzing 189 Methylobacterium genomes from a wide range of habitats, including the phyllosphere, we inferred a robust phylogenetic tree while explicitly accounting for the impact of horizontal gene transfer (HGT). We showed that Methylobacterium contains four evolutionarily distinct groups of bacteria (namely A, B, C, D), characterized by different genome size, GC content, gene content, and genome architecture, revealing the dynamic nature of Methylobacterium genomes. In addition to recovering 59 described species, we identified 45 candidate species, mostly phyllosphere-associated, stressing the significance of plants as a reservoir of Methylobacterium diversity. We inferred an ancient transition from a free-living lifestyle to association with plant roots in Methylobacteriaceae ancestor, followed by phyllosphere association of three of the major groups (A, B, D), whose early branching in Methylobacterium history has been heavily obscured by HGT. Together, our work lays the foundations for a thorough redefinition of Methylobacterium taxonomy, beginning with the abandonment of Methylorubrum.

Building digital twins of the human immune system: toward a roadmap.

Digital twins, customized simulation models pioneered in industry, are beginning to be deployed in medicine and healthcare, with some major successes, for instance in cardiovascular diagnostics and in insulin pump control. Personalized computational models are also assisting in applications ranging from drug development to treatment optimization. More advanced medical digital twins will be essential to making precision medicine a reality. Because the immune system plays an important role in such a wide range of diseases and health conditions, from fighting pathogens to autoimmune disorders, digital twins of the immune system will have an especially high impact. However, their development presents major challenges, stemming from the inherent complexity of the immune system and the difficulty of measuring many aspects of a patient's immune state in vivo. This perspective outlines a roadmap for meeting these challenges and building a prototype of an immune digital twin. It is structured as a four-stage process that proceeds from a specification of a concrete use case to model constructions, personalization, and continued improvement.

Comparing microscopy and DNA metabarcoding techniques for identifying cyanobacteria assemblages across hundreds of lakes.

Accurately identifying the species present in an ecosystem is vital to lake managers and successful bioassessment programs. This is particularly important when monitoring cyanobacteria, as numerous taxa produce toxins and can have major negative impacts on aquatic ecosystems. Increasingly, DNA-based techniques such as metabarcoding are being used for measuring aquatic biodiversity, as they could accelerate processing time, decrease costs and reduce some of the biases associated with traditional light microscopy. Despite the continuing use of traditional microscopy and the growing use of DNA metabarcoding to identify cyanobacteria assemblages, methodological comparisons between the two approaches have rarely been reported from a wide suite of lake types. Here, we compare planktonic cyanobacteria assemblages generated by inverted light microscopy and DNA metabarcoding from a 379-lake dataset spanning a longitudinal and trophic gradient. We found moderate levels of congruence between methods at the broadest taxonomic levels (i.e., Order, RV=0.40, p < 0.0001). This comparison revealed distinct cyanobacteria communities from lakes of different trophic states, with Microcystis, Aphanizomenon and Dolichospermum dominating with both methods in eutrophic and hypereutrophic sites. This finding supports the use of either method when monitoring eutrophication in lake surface waters. The biggest difference between the two methods was the detection of picocyanobacteria, which are typically underestimated by light microscopy. This reveals that the communities generated by each method currently are complementary as opposed to identical and promotes a combined-method strategy when monitoring a range of trophic systems. For example, microscopy can provide measures of cyanobacteria biomass, which are critical data in managing lakes. Going forward, we believe that molecular genetic methods will be increasingly adopted as reference databases are routinely updated with more representative sequences and will improve as cyanobacteria taxonomy is resolved with the increase in available genetic information.

Population Genomics Approaches for Genetic Characterization of SARS-CoV-2 Lineages.

The genome of the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), the pathogen that causes coronavirus disease 2019 (COVID-19), has been sequenced at an unprecedented scale leading to a tremendous amount of viral genome sequencing data. To assist in tracing infection pathways and design preventive strategies, a deep understanding of the viral genetic diversity landscape is needed. We present here a set of genomic surveillance tools from population genetics which can be used to better understand the evolution of this virus in humans. To illustrate the utility of this toolbox, we detail an in depth analysis of the genetic diversity of SARS-CoV-2 in first year of the COVID-19 pandemic. We analyzed 329,854 high-quality consensus sequences published in the GISAID database during the pre-vaccination phase. We demonstrate that, compared to standard phylogenetic approaches, haplotype networks can be computed efficiently on much larger datasets. This approach enables real-time lineage identification, a clear description of the relationship between variants of concern, and efficient detection of recurrent mutations. Furthermore, time series change of Tajima's D by haplotype provides a powerful metric of lineage expansion. Finally, principal component analysis (PCA) highlights key steps in variant emergence and facilitates the visualization of genomic variation in the context of SARS-CoV-2 diversity. The computational framework presented here is simple to implement and insightful for real-time genomic surveillance of SARS-CoV-2 and could be applied to any pathogen that threatens the health of populations of humans and other organisms.