Venkata Rami Reddy Emani, Vivek Krishnamani Pallipuram, Kartik Kumar Goswami, Kailash Reddy Maddula, Raghunath Reddy, Abirath Surender Nakka, Sravya Panga, Nikhila Komati Reddy, Nidhi Komati Reddy, Dheeraj Nandanoor, Sanjeev Goswami

BACKGROUND There were increased SARS-CoV2 hospitalizations and deaths noted during Omicron (B.1.1.529) variant surge in UK despite decreased cases, and the reasons are unclear. METHODS In this observational study, we analyzed reported SARS-CoV2 cases, hospitalizations and deaths during the COVID-19 pandemic in the UK. We also analyzed variables that can affect the outcomes. The vaccine effectiveness among those [&ge;]18 years of age (August 16, 2021 to March 27, 2022) was analyzed. RESULTS Of the total cases (n= 22,072,550), hospitalizations (n=848,911) and deaths (n=175,070) due to COVID-19 in UK; 51.3% of cases (n=11,315,793), 28.8% of hospitalizations (n=244,708) and 16.4% of deaths (n=28,659) occurred during Omicron variant surge. When comparing the period of February 28-May 1, 2022 with the prior 12-weeks, we observed a significant increase in the case fatality rate (0.19% vs 0.41%; RR 2.11[ 2.06-2.16], p<0.001) and odds of hospitalization (1.58% vs 3.72%; RR 2.36[2.34-2.38]; p<0.001). During the same period a significant increase in cases (23.7% vs 40.3%; RR1.70 [1.70-1.71]; p<0.001) among [&ge;]50 years of age and hospitalizations (39.3% vs 50.3%;RR1.28 [1.27-1.30]; p<0.001) and deaths (67.89% vs 80.07%;RR1.18 [1.16-1.20]; p<0.001) among [&ge;]75 years of age was observed. The vaccine effectiveness (VE) for the third dose was in negative since December 20, 2021, with a significantly increased proportion of SARS-CoV2 cases hospitalizations and deaths among the vaccinated; and a decreased proportion of cases, hospitalizations, and deaths among the unvaccinated. The pre-existing conditions were present in 95.6% of all COVID-19 deaths, various ethnic, deprivation score and vaccination rate disparities noted that can adversely affect hospitalization and deaths among compared groups. CONCLUSIONS There is no discernable vaccine effectiveness among [&ge;]18 years of age, vaccinated third dose population since the beginning of the Omicron variant surge. Pre-existing conditions, ethnicity, deprivation score, and vaccination rate disparities data need to be adjusted for evaluating VE for hospitalizations and deaths. The increased cases with significantly increased hospitalizations and deaths among the elderly population during the Omicron variant surge underscores the need to prevent infections in the elderly irrespective of vaccination status with uniform screening protocols and protective measures.

Vincent Larivière, Véronique Kiermer, Catriona J. MacCallum, Marcia McNutt, Mark Patterson, Bernd Pulverer, Sowmya Swaminathan, Stuart Taylor, Stephen Curry

Although the Journal Impact Factor (JIF) is widely acknowledged to be a poor indicator of the quality of individual papers, it is used routinely to evaluate research and researchers. Here, we present a simple method for generating the citation distributions that underlie JIFs. Application of this straightforward protocol reveals the full extent of the skew of these distributions and the variation in citations received by published papers that is characteristic of all scientific journals. Although there are differences among journals across the spectrum of JIFs, the citation distributions overlap extensively, demonstrating that the citation performance of individual papers cannot be inferred from the JIF. We propose that this methodology be adopted by all journals as a move to greater transparency, one that should help to refocus attention on individual pieces of work and counter the inappropriate usage of JIFs during the process of research assessment.

Yanmei Hu, Eric M Lewandowski, Haozhou Tan, Ryan T Morgan, Xiujun Zhang, Lian M Jacobs, Shane G Butler, Maura V Mongora, John S. Choy, Yu Chen, Jun Wang

The SARS-CoV-2 main protease (Mpro) is a cysteine protease and a validated antiviral drug target. Paxlovid is an FDA-approved oral COVID-19 antiviral that contains the Mpro inhibitor nirmatrelvir and the metabolic booster ritonavir. The emergence of SARS-CoV-2 variants mutations in the Mpro raised the alarm of potential drug resistance. In this study, we aim to discover Mpro drug resistant mutants from naturally observed polymorphisms. Through analyzing the SARS-CoV-2 sequences deposited in Global initiative on Sharing Avian influenza Data (GISAID) database, we identified 66 prevalent Mpro mutations located at the nirmatrelvir binding site. The Mpro mutant proteins were expressed and characterized for enzymatic activity and nirmatrelvir inhibition. While the majority of the Mpro mutants had reduced enzymatic activity (kcat/Km >10-fold decrease), 11 mutants including S144M/F/A/G/Y, M165T, E166Q, H172Q/F, and Q192T/S/V showed comparable enzymatic activity as the wild-type (kcat/Km <10-fold change) and resistance to nirmatrelvir (Ki > 10-fold increase). We further demonstrate that the enzymatic activity and inhibitor resistance of these single mutations can be enhanced by additional substitutions in a double mutant. X-ray crystal structures were determined for six of the single mutants with and/or without GC-376/nirmatrelvir. The structures illustrate how mutations can reduce ligand binding by impacting the conformational stability of the active site. Overall, our study identified several drug resistant hot spots that warrant close monitoring for possible clinical evidence of Paxlovid resistance.

Tal Patalon, Yaki Saciuk, Hanit Ohayon Hadad, Galit Perez, Asaf Peretz, Amir Ben-Tov, Sivan Gazit

Objectives: There are paucity of studies examining naturally acquired immunity against SARS-CoV-2 in children and adolescents, though they are generally the last group to be afforded the vaccine, and a significant portion of them are still unvaccinated. This study examined the duration of protection conferred by a previous SARS-CoV-2 infection amongst children and adolescents. Design: A retrospective study, applying two complementary approaches: a matched test-negative case control design and a retrospective cohort design. Setting: Nationally centralized database of Maccabi Healthcare Services, an Israeli national health fund that covers 2.5 million people. Participants: The study population included between 293,743 and 458,959 individuals (depending on the model), 5-18 years of age, who were unvaccinated SARS-CoV-2 naive persons or unvaccinated convalescent patients. Main outcomes and measures: Analyses focused on the period of July 1 to December 13, 2021, a Delta-dominant period in Israel. We evaluated three SARS-CoV-2-related outcomes: (1) documented PCR confirmed infection or reinfection, (2) COVID-19 and (3) severe COVID-19. Results: Overall, children and adolescents who were previously infected acquired durable protection against reinfection (symptomatic or not) with SARS-CoV-2 for at least 18 months. Importantly, no COVID-19 related deaths were recorded in either the SARS-CoV-2 naive group or the previously infected group. Effectiveness of naturally-acquired immunity against a recurrent infection reached 89.2% (95% CI: 84.7%-92.4%) three to six months after first infection, mildly declining to 82.5% (95% CI, 79.1%-85.3%) nine months to one year after infection, then remaining rather steady for children and adolescents for up to 18 months, with a slight non-significant waning trend. Additionally, we found that ages 5-11 exhibited no significant waning of naturally acquired protection throughout the outcome period, whereas waning protection in the 12-18 age group was more prominent, but still mild. Conclusions: Children and adolescents who were previously infected with SARS-CoV-2 remain protected against reinfection to a high degree for 18 months. Policy decision makers should consider when and if convalescent children and adolescents should be vaccinated. Nonetheless, further research is needed to examine naturally acquired immunity against emerging variants, including the Omicron.

Douglas F Browning, Jon L Hobman, Stephen JW Busby

Escherichia coli K-12 was originally isolated 100 years ago and since then, it has become an invaluable model organism and a cornerstone of molecular biology research. However, despite its apparent pedigree, since its initial isolation, E. coli K-12 has been repeatedly cultured, passaged, and mutagenized, resulting in an organism that carries extensive genetic changes. To understand more about the evolution of this important model organism, we have sequenced the genomes of two ancestral K-12 strains, WG1 and EMG2, considered to be the progenitors of many key laboratory strains. Our analysis confirms that these strains still carry genetic elements such as bacteriophage lambda ({lambda}) and the F plasmid, but also indicates that they have undergone extensive lab-based evolution. Thus, scrutinizing the genomes of ancestral E. coli K-12 strains, leads us to question whether E. coli K-12 is a sufficiently robust model organism for 21st century microbiology.

Gautam Upadhya, Matthias Steinruecken

Unraveling the complex demographic histories of natural populations is a central problem in population genetics. Understanding past demographic events is of general anthropological interest, but is also an important step in establishing accurate null models when identifying adaptive or disease-associated genetic variation. An important class of tools for inferring past population size changes from genomic sequence data are Coalescent Hidden Markov Models (CHMMs). These models make efficient use of the linkage information in population genomic datasets by using the local genealogies relating sampled individuals as latent states that evolve along the chromosome in an HMM framework. Extending these models to large sample sizes is challenging, since the number of possible latent states increases rapidly. Here, we present our method CHIMP (CHMM History-Inference Maximum-Likelihood Procedure), a novel CHMM method for inferring the size history of a population. It can be applied to large samples (hundreds of haplotypes) and only requires unphased genomes as input. The two implementations of CHIMP that we present here use either the height of the genealogical tree (TMRCA) or the total branch length, respectively, as the latent variable at each position in the genome. The requisite transition and emission probabilities are obtained by numerically solving certain systems of differential equations derived from the ancestral process with recombination. The parameters of the population size history are subsequently inferred using an Expectation-Maximization algorithm. In addition, we implement a composite likelihood scheme to allow the method to scale to large sample sizes. We demonstrate the efficiency and accuracy of our method in a variety of benchmark tests using simulated data and present comparisons to other state-of-the-art methods. Specifically, our implementation using TMRCA as the latent variable shows comparable performance and provides accurate estimates of effective population sizes in intermediate and ancient times. Our method is agnostic to the phasing of the data, which makes it a promising alternative in scenarios where high quality data is not available, and has potential applications for pseudo-haploid data.

Marc Conrad Shamier, Alma Tostmann, Susanne Bogers, Janet De Wilde, Jeroen IJpelaar, Willemijn Van Der Kleij, Herbert De Jager, Bart Haagmans, Richard Molenkamp, Bas Oude Munnink, Carsten van Rossum, Janette Rahamat-Langendoen, Nannet Van Der Geest, Chantal Bleeker-Rovers, Heiman F.L. Wertheim, Marion Koopmans, Corine GeurtsvanKessel

SARS-CoV-2 vaccines are highly effective at preventing COVID-19-related morbidity and mortality. As no vaccine is 100% effective, breakthrough infections are expected to occur. We analyzed the virological characteristics of 161 vaccine breakthrough infections in a population of 24,706 vaccinated healthcare workers (HCWs), using RT-PCR and virus culture. The delta variant (B.1.617.2) was identified in the majority of cases. Despite similar Ct-values, we demonstrate lower probability of infectious virus detection in respiratory samples of vaccinated HCWs with breakthrough infections compared to unvaccinated HCWs with primary SARS-CoV-2 infections. Nevertheless, infectious virus was found in 68.6% of breakthrough infections and Ct-values decreased throughout the first 3 days of illness. We conclude that rare vaccine breakthrough infections occur, but infectious virus shedding is reduced in these cases.

Evlyn Pless, Anders M Eckburg, Brenna M Henn

Landscape, climate, and culture can all structure human populations, but few methods are designed to disentangle the importance of these many variables. We developed a machine learning method for identifying the variables which best explain migration rates, as measured by the coalescent-based program MAPS that uses shared identical by descent tracts to infer and extrapolate spatial migration across a region of interest. We applied our method to 30 human populations in eastern Africa with high density SNP array data. The remarkable diversity of ethnicities, languages, and environments in this region offers a unique opportunity to explore the variables that shape migration and genetic structure in humans. We explored more than twenty spatial variables relating to landscape, climate, and presence of tsetse flies (an important regional disease vector). The full model explained ~40% of variance in migration rate over the past 56 generations. Precipitation, minimum temperature of the coldest month, and altitude were the most important variables. Among the three groups of tsetse flies, the most important was the fusca group which is a vector for livestock trypanosomiasis. We also performed a selection scan on a subgroup of the populations who live in Ethiopia at relatively high altitudes. We did not identify well-known high-altitude genes, but we did find signatures of positive selection related to metabolism and disease (e.g. PNPLA2 and IRF4). We conclude that environment and landscape has notably shaped the migration and adaptation of human populations in eastern Africa; the remaining variance in structure is likely due to cultural factors not captured in our model.

Yu Wang, Yuexing Liu

The World Health Organization have recently announced outbreak news of acute, severe hepatitis of unknown cause in children under a Covid-19 pandemic. Whether it is associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is still under debating. Here, we performed genomic sequence alignment analysis of the genome of SARS-Cov-2 (Wuhan-hu-1) to the human genome reference. Sequence analysis revealed that the SARS-CoV-2 ORF1ab1056-1173 presented high identities with the human protein PAPR1453-176(3Q6Z_A). After searching the fully sequenced SARS-CoV-2 genomes deposited in GISAID (https://www.gisaid.org/), we detected 170 SARS-CoV-2 variants with mutation in ORF1ab1061, where alanine (A) was substituted by serine (S). This alteration made a 7-amino acid peptide (VVVNASN) in ORF1ab1056-1062 identical to its counterpart in PARP1453-59(3Q6Z_A). HLA prediction suggested that the peptides with high identities in PARP14 and ORF1ab could be presented by a same globally prevalent HLA-A*11:01 molecule. And in consistent with the first reported case of hepatitis of unknown, SARS-CoV-2 ORF1abVVVNASN variants were mostly identified as Delta lineages in UK by the late 2021, with an overall frequency of 0.00161%. Thus, our preliminary results raised a possibility that infection by SARS-CoV-2 ORF1abVVVNASN variant might elicit an autoimmune T cell response via epitope mimicry and is associated with the outbreak of unknown hepatitis. We anticipated that these findings will alert the human societies to pay more attention to rare mutations beyond the spike proteins.

Wenxin Tong, Sarah A Hannou, You Wang, Inna Astapova, Ashot Sargsyan, Ruby Monn, Venkataramana Thiriveedi, Diana Li, Jessica R McCann, John F Rawls, Jatin Roper, Guo-Fang Zhang, Mark A Herman

The tricarboxylic acid (TCA) cycle is the epicenter of cellular aerobic metabolism. TCA cycle intermediates facilitate energy production and provide anabolic precursors, but also function as intra- and extracellular metabolic signals regulating pleiotropic biological processes. Despite the importance of circulating TCA cycle metabolites as signaling molecules, the source of circulating TCA cycle intermediates remains uncertain. We observe that in mice, the concentration of TCA cycle intermediates in the portal blood exceeds that in tail blood indicating that the gut is a major contributor to circulating TCA cycle metabolites. With a focus on succinate as a representative of TCA cycle intermediate with signaling activities and using a combination of germ-free mice and isotopomer tracing, we demonstrate that intestinal microbiota are not major contributors to circulating TCA cycle metabolites. Moreover, we demonstrate that the endogenous succinate production is markedly higher than intestinal succinate absorption in normal physiological conditions. Altogether, these results indicate that endogenous succinate production within the intestinal tissue is a major physiological source of circulating succinate. These results provide a foundation for investigation into the role of intestine in regulating circulating TCA cycle metabolites and related signaling effects in health and disease.

Martina Patone, Winnie Xue Mei, Lahiru Handunnetthi, Sharon Dixon, Francesco Zaccardi, Manu Shankar-Hari, Peter Watkinson, Kamlesh Khunti, Anthony Harnden, Carol AC Coupland, Keith M Channon, Nicholas L Mills, Aziz Sheikh, Julia Hippisley-Cox

In an updated self-controlled case series analysis of 42,200,614 people aged 13 years or more, we evaluate the association between COVID-19 vaccination and myocarditis, stratified by age and sex, including 10,978,507 people receiving a third vaccine dose. Myocarditis risk was increased during 1-28 days following a third dose of BNT162b2 (IRR 2.02, 95%CI 1.40, 2.91). Associations were strongest in males younger than 40 years for all vaccine types with an additional 3 (95%CI 1, 5) and 12 (95% CI 1,17) events per million estimated in the 1-28 days following a first dose of BNT162b2 and mRNA-1273, respectively; 14 (95%CI 8, 17), 12 (95%CI 1, 7) and 101 (95%CI 95, 104) additional events following a second dose of ChAdOx1, BNT162b2 and mRNA-1273, respectively; and 13 (95%CI 7, 15) additional events following a third dose of BNT162b2, compared with 7 (95%CI 2, 11) additional events following COVID-19 infection. An association between COVID-19 infection and myocarditis was observed in all ages for both sexes but was substantially higher in those older than 40 years. These findings have important implications for public health and vaccination policy.

Pascal Miesen, Samara Rosendo Machado, Jieqiong Qu, Werner J.H. Koopman

Aedes aegypti mosquitoes are responsible for the transmission of arthropod-borne (arbo)viruses including dengue and chikungunya virus (CHIKV), but in contrast to human hosts, arbovirus infected mosquitoes are able to efficiently control virus replication to sub-pathological levels. Yet, our knowledge about the molecular interactions of arboviruses with their mosquito hosts is largely incomplete. Here, we aimed to identify and characterize novel host genes that control arbovirus replication in Aedes mosquitoes. RNA binding proteins (RBPs) are well known to regulate immune signaling pathways in all kingdoms of life. We therefore performed a knockdown screen targeting 461 genes encoding predicted RBPs in Aedes aegypti Aag2 cells and identified 15 genes with antiviral activity against a Sindbis reporter virus. Amongst these, three DEAD-box RNA helicases, AAEL004419/Dhx15, AAEL008728 and AAEL004859 also acted as antiviral factors in dengue and CHIKV infections. Here, we explore the mechanism of Dhx15 in regulating an antiviral transcriptional response in mosquitoes by silencing Dhx15 in Aag2 cells followed by deep-sequencing of poly-A enriched RNAs. Dhx15 knockdown in uninfected or CHIKV-infected cells resulted in differential expression of 856 and 372 genes, respectively. Interestingly, amongst the consistently downregulated genes, glycolytic process was the most strongly enriched GO term as the expression of all core enzymes of the glycolytic pathway was reduced, suggesting that Dhx15 regulates glycolytic function. A decrease in lactate production supported the observation that Dhx15 silencing functionally impaired glycolysis. Modified rates of glycolytic metabolism have been implicated in controlling the replication of several classes of viruses and strikingly, infection of Aag2 cells with CHIKV by itself also resulted in the decrease of several glycolysis genes. Our data suggests that Dhx15 regulates replication of CHIKV, and possibly other arboviruses, by controlling glycolysis in mosquito cells.

Haiyue Ai, Julia Bellstaedt, Kai Steffen Bartusch, Lennart Eschen-Lippold, Steve Babben, Gerd Ulrich Balcke, Alain Tissier, Bettina Hause, Tonni Grube Andersen, Carolin Delker, Marcel Quint

Roots are highly plastic organs enabling plants to acclimate to a changing below-ground environment. In addition to abiotic factors like nutrients or mechanical resistance, plant roots also respond to temperature variation. Below the heat stress threshold, Arabidopsis thaliana seedlings react to elevated temperature by promoting primary root growth, possibly to reach deeper soil regions with potentially better water saturation. While above-ground thermomorphogenesis is enabled by thermo-sensitive cell elongation, it was unknown how temperature modulates root growth. We here show that roots are able to sense and respond to elevated temperature independent of shoot-derived signals. A yet unknown root thermosensor seems to employ auxin as a messenger to promote primary root growth. Growth is primarily achieved by accelerating cell division rates in the root apical meristem, likely maintained via temperature-sensitive organization of the polar auxin transport system. Hence, the primary cellular target of elevated ambient temperature differs fundamentally between root and shoot tissues, while the messenger auxin that relays temperature information to elongating or dividing cells, respectively, remains the same.

Yiwei Zhang, Karl Johnson, Zhuoting Yu, Akane Fujimoto, Kristen Hassmiller Lich, Julie Ivy, Pinar Keskinocak, Maria Mayorga, Julie L Swann

Background: Millions of primary school students across the United States are about to return to in-person learning. Amidst circulation of the highly infectious Delta variant, there is danger that without the appropriate safety precautions, substantial amount of school-based spread of COVID-19 may occur. Methods: We used an extended Susceptible-Infected-Recovered computational model to estimate the number of new infections during 1 semester among a student population under different assumptions about mask usage, routine testing, and levels of incoming protection. Our analysis considers three levels of incoming protection (30%, 40%, or 50%; denoted as "low", "mid", or "high"). Universal mask usage decreases infectivity by 50%, and weekly testing may occur among 50% of the student population; positive tests prompt quarantine until recovery, with compliance contingent on symptom status. Results: Without masking and testing, more than 75% of susceptible students become get infected within three months in all settings. With masking, this values decreases to 50% for "low" incoming protection settings ("mid"=35%, "high"=24%). Testing half the masked population ("testing") further drops infections to 22% (16%, 13%). Conclusion: Without interventions in place, the vast majority of susceptible students will become infected through the semester. Universal masking can reduce student infections by 26-78%, and biweekly testing along with masking reduces infections by another 50%. To prevent new infections in the community, limit school absences, and maintain in-person learning, interventions such as masking and testing must be implemented widely, especially among elementary school settings in which children are not yet eligible for the vaccine.

Gavin Leech, Charlie Rogers-Smith, Jonas Benjamin Sandbrink, Benedict Snodin, Robert Zinkov, Benjamin M Rader, John S Brownstein, Yarin Gal, Samir Bhatt, Mrinank Sharma, Soren Mindermann, Jan Markus Brauner, Laurence Aitchison

Mask-wearing has been a controversial measure to control the COVID-19 pandemic. While masks are known to substantially reduce disease transmission in healthcare settings (Howard et al 2021), studies in community settings report inconsistent results (Brainard et al 2020). Investigating the inconsistency within epidemiological studies, we find that a commonly used proxy, government mask mandates, does not correlate with large increases in mask-wearing in our window of analysis. We thus analyse the effect of mask-wearing on transmission instead, drawing on several datasets covering 92 regions on 6 continents, including the largest survey of individual-level wearing behaviour (n=20 million) (Kreuter et al 2020). Using a hierarchical Bayesian model, we estimate the effect of both mask-wearing and mask-mandates on transmission by linking wearing levels (or mandates) to reported cases in each region, adjusting for mobility and non-pharmaceutical interventions. We assess the robustness of our results in 123 experiments across 22 sensitivity analyses. Across these analyses, we find that an entire population wearing masks in public leads to a median reduction in the reproduction number R of 25.8%, with 95% of the medians between 22.2% and 30.9%. In our window of analysis, the median reduction in $R$ associated with the wearing level observed in each region was 20.4% [2.0%, 23.3%]. We do not find evidence that mandating mask-wearing reduces transmission. Our results suggest that mask-wearing is strongly affected by factors other than mandates. We establish the effectiveness of mass mask-wearing, and highlight that wearing data, not mandate data, are necessary to infer this effect.

Arpita Sarkar, Sophie Lanciano, Gael Cristofari

Retrotransposition of LINE-1 (L1) elements represent a major source of insertional polymorphisms in mammals and their mutagenic activity is restricted by silencing mechanisms, such as DNA methylation. Despite a very high level of sequence identity between copies, their internal sequence contains small nucleotide polymorphisms (SNPs) that can alter their activity. Such internal SNPs can also appear in different alleles of a given L1 locus. Given their repetitive nature and relatively long size, short-read sequencing approaches have limited access to L1 internal sequence or DNA methylation state. Here we describe a targeted method to specifically sequence more than a hundred L1-containing loci in parallel and measure their DNA methylation levels using nanopore long-read sequencing. Each targeted locus is sequenced at high coverage (~45X) with unambiguously mapped reads spanning the entire L1 element, as well as its flanking sequences over several kilobases. Our protocol, modified from the nanopore Cas9 targeted sequencing (nCATS) strategy, provides a full and haplotype-resolved L1 sequence and DNA methylation levels. It introduces a streamlined and multiplex approach to synthesize guide RNAs and a quantitative PCR (qPCR)-based quality check during library preparation for cost-effective L1 sequencing. More generally, this method can be applied to any type of transposable elements and organisms.

Lucas Robidou, Pierre Peterlongo

Approximate membership query data structures (AMQ) such as Cuckoo filters or Bloom filters are widely used for representing and indexing large sets of elements. AMQ can be generalized for additionally counting indexed elements, they are then called "counting AMQ". This is for instance the case of the "counting Bloom filters". However, counting AMQs suffer from false positive and overestimated calls. In this work we propose a novel computation method, called fimpera, consisting of a simple strategy for reducing the false-positive rate of any AMQ indexing all k-mers (words of length k) from a set of sequences, along with their abundance information. This method decreases the false-positive rate of a counting Bloom filter by an order of magnitude while reducing the number of overestimated calls, as well as lowering the average difference between the overestimated calls and the ground truth. In addition, it slightly decreases the query run time. fimpera does not require any modification of the original counting Bloom filter, it does not generate false-negative calls, and it causes no memory overhead. The unique drawback is that fimpera yields a new kind of false positives and overestimated calls. However their amount is negligible. fimpera requires a unique parameter, and its results are only little impacted when using this parameter within recommended values. As a side note, for the algorithmic needs of the method, we also propose a novel generic algorithm for finding minimal values of a sliding window over a vector of x integers in O(x) time with zero memory allocation.

Raman Akinyanju Lawal, Verity L Mathis, Mary E. Barter, Jeremy R. Charette, Alexis Garretson, Beth L Dumont

House mice (Mus musculus) are comprised of three primary subspecies. A large number of secondary subspecies have also been suggested on the basis of divergent morphology and molecular variation at limited numbers of markers. While the phylogenetic relationships among the primary M. musculus subspecies are well-defined, the relationships among the secondary subspecies, and their relationships to primary subspecies, remain poorly understood. Here, we integrate de novo genome sequencing of museum-stored specimens of house mice from one secondary subspecies (M. m. bactrianus) and publicly available genome sequences of house mice previously characterized as M. m. helgolandicus, with whole-genome sequences from diverse representatives of the three primary house mouse subspecies. We show that mice assigned to the secondary M. m. bactrianus and M. m. helgolandicus subspecies are not genetically differentiated from the contemporary M. m. castaneus and M. m. domesticus, respectively. Overall, our work suggests that the M. m. bactrianus and M. m. helgolandicus subspecies are not well-justified taxonomic entities, emphasizing the importance of leveraging whole-genome sequence data to inform subspecies designations. Additionally, our investigation has established experimental procedures for generating whole-genome sequences from air-dried museum specimens and provides key genomic resources to inform future genomic investigations of wild mouse diversity.

Tony Pan, Guoshuai Cao, Erting Tang, Yu zhao, Pablo Penaloza-MacMaster, Yun Fang, Jun Huang

SARS-CoV-2 and HIV-1 are RNA viruses that have killed millions of people worldwide. Understanding the similarities and differences between these two infections is critical for understanding disease progression and for developing effective vaccines and therapies, particularly for 38 million HIV-1+ individuals who are vulnerable to SARS-CoV-2 co-infection. Here, we utilized single-cell transcriptomics to perform a systematic comparison of 94,442 PBMCs from 7 COVID-19 and 9 HIV-1+ patients in an integrated immune atlas, in which 27 different cell types were identified using an accurate consensus single-cell annotation method. While immune cells in both cohorts show shared inflammation and disrupted mitochondrial function, COVID-19 patients exhibit stronger humoral immunity, broader IFN-I signaling, elevated Rho GTPase and mTOR pathway activities, and downregulated mitophagy. Our results elucidate transcriptional signatures associated with COVID-19 and HIV-1 that may reveal insights into fundamental disease biology and potential therapeutic targets to treat these viral infections.

Justin P Shaffer, Louis-Félix Nothias, Luke R Thompson, Sanders G Jon, Rodolfo A. Salido, Sneha P Couvillion, Asker D Brejnrod, Shi Huang, Franck Lejzerowicz, Niina Haiminen, Holly L Lutz, Qiyun Zhu, Cameron Martino, James T Morton, Smruthi Karthikeyan, Mélissa Nothias-Esposito, Kai Dührkop, Sebastian Böcker, Hyunwoo Kim, Alexander A Aksenov, Wout Bittremieux, Jeremiah J Minich, Clarisse Marotz, MacKenzie M Bryant, Karenina Sanders, Tara Schwartz, Greg Humphrey, Yoshiki Vasquez-Baeza, Anupriya Tripathi, Laxmi Parida, Anna Paola Carrieri, Kristen L. Beck, Promi Das, Antonio Gonzalez, Daniel McDonald, Søren Michael Karst, Mads Albertsen, Gail Ackermann, Jeff DeReus, Torsten Thomas, Daniel Petras, Ashley Shade, James Stegen, Se Jin Song, Thomas O Metz, Austin D Swafford, Pieter C. Dorrestein, Janet K. Jansson, Jack A Gilbert, Rob Knight, The Earth Microbiome Project 500 (EMP500) Consortium

As our understanding of the structure and diversity of the microbial world grows, interpreting its function is of critical interest for understanding and managing the many systems microbes influence. Despite advances in sequencing, lack of standardization challenges comparisons among studies that could provide insight into the structure and function of microbial communities across multiple habitats on a planetary scale. Technical variation among distinct studies without proper standardization of approaches prevents robust meta-analysis. Here, we present a multi-omics, meta-analysis of a novel, diverse set of microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry), centering our description on relationships and co-occurrences of microbially-related metabolites and microbial taxa across environments. Standardized protocols and analytical methods for characterizing microbial communities, including assessment of molecular diversity using untargeted metabolomics, facilitate identification of shared microbial and metabolite features, permitting us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of a community resource that will become more valuable with time. To provide examples of applying this database, we outline important ecological questions that can be addressed, and test the hypotheses that every microbe and metabolite is everywhere, but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment. The relative abundances of microbially-related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner, and highlight the power of certain chemistry - in particular terpenoids - in distinguishing Earth's environments.