Navigating bottlenecks and trade-offs in genomic data analysis.

Genome sequencing and analysis allow researchers to decode the functional information hidden in DNA sequences as well as to study cell to cell variation within a cell population. Traditionally, the primary bottleneck in genomic analysis pipelines has been the sequencing itself, which has been much more expensive than the computational analyses that follow. However, an important consequence of the continued drive to expand the throughput of sequencing platforms at lower cost is that often the analytical pipelines are struggling to keep up with the sheer amount of raw data produced. Computational cost and efficiency have thus become of ever increasing importance. Recent methodological advances, such as data sketching, accelerators and domain-specific libraries/languages, promise to address these modern computational challenges. However, despite being more efficient, these innovations come with a new set of trade-offs, both expected, such as accuracy versus memory and expense versus time, and more subtle, including the human expertise needed to use non-standard programming interfaces and set up complex infrastructure. In this Review, we discuss how to navigate these new methodological advances and their trade-offs.

Proving sequence aligners can guarantee accuracy in almost O(m log n) time through an average-case analysis of the seed-chain-extend heuristic.

Seed-chain-extend with k-mer seeds is a powerful heuristic technique for sequence alignment used by modern sequence aligners. Although effective in practice for both runtime and accuracy, theoretical guarantees on the resulting alignment do not exist for seed-chain-extend. In this work, we give the first rigorous bounds for the efficacy of seed-chain-extend with k-mers in expectation Assume we are given a random nucleotide sequence of length ∼n that is indexed (or seeded) and a mutated substring of length ∼m ≤ n with mutation rate θ < 0.206. We prove that we can find a k = Θ(log n) for the k-mer size such that the expected runtime of seed-chain-extend under optimal linear-gap cost chaining and quadratic time gap extension is O(mn f (θ) log n), where f(θ) < 2.43 · θ holds as a loose bound. The alignment also turns out to be good; we prove that more than [Formula: see text] fraction of the homologous bases is recoverable under an optimal chain. We also show that our bounds work when k-mers are sketched, that is, only a subset of all k-mers is selected, and that sketching reduces chaining time without increasing alignment time or decreasing accuracy too much, justifying the effectiveness of sketching as a practical speedup in sequence alignment. We verify our results in simulation and on real noisy long-read data and show that our theoretical runtimes can predict real runtimes accurately. We conjecture that our bounds can be improved further, and in particular, f(θ) can be further reduced.

Fast and robust metagenomic sequence comparison through sparse chaining with skani.

Sequence comparison tools for metagenome-assembled genomes (MAGs) struggle with high-volume or low-quality data. We present skani ( https://github.com/bluenote-1577/skani ), a method for determining average nucleotide identity (ANI) via sparse approximate alignments. skani outperforms FastANI in accuracy and speed (>20× faster) for fragmented, incomplete MAGs. skani can query genomes against >65,000 prokaryotic genomes in seconds and 6 GB memory. skani unlocks higher-resolution insights for extensive, noisy metagenomic datasets.

Author Correction: The Apostasia genome and the evolution of orchids.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Complement contributes to antibody-mediated protection against repeated SHIV challenge.

The first clinical efficacy trials of a broadly neutralizing antibody (bNAb) resulted in less benefit than expected and suggested that improvements are needed to prevent HIV infection. While considerable effort has focused on optimizing neutralization breadth and potency, it remains unclear whether augmenting the effector functions elicited by broadly neutralizing antibodies (bNAbs) may also improve their clinical potential. Among these effector functions, complement-mediated activities, which can culminate in the lysis of virions or infected cells, have been the least well studied. Here, functionally modified variants of the second-generation bNAb 10-1074 with ablated and enhanced complement activation profiles were used to examine the role of complement-associated effector functions. When administered prophylactically against simian-HIV challenge in rhesus macaques, more bNAb was required to prevent plasma viremia when complement activity was eliminated. Conversely, less bNAb was required to protect animals from plasma viremia when complement activity was enhanced. These results suggest that complement-mediated effector functions contribute to in vivo antiviral activity, and that their engineering may contribute to the further improvements in the efficacy of antibody-mediated prevention strategies.

Sodium-glucose cotransporter-2 inhibitors and their potential role in dementia onset and cognitive function in patients with diabetes mellitus: a systematic review and meta-analysis.

This systematic review and meta-analysis aimed to determine the association between the use of sodium-glucose cotransporter 2 (SGLT-2) inhibitors and dementia onset as well as cognitive function in patients with diabetes mellitus. We comprehensively searched the MEDLINE, Embase, and CENTRAL databases to select relevant studies published up to August 2023. The use of SGLT-2 inhibitors significantly lowers dementia risk compared to SGLT-2i non-users (Hazard ratio: 0.68, 95 % CI: 0.50-0.92). Furthermore, our findings indicated a positive effect of SGLT-2 inhibitor use on cognitive function score improvement, as demonstrated by the standardized mean difference of 0.88 (95 % CI: 0.32-1.44), particularly among populations with mild cognitive impairment or dementia. This systematic review and meta-analysis indicate a potential role of SGLT-2 inhibitors in reducing the risk of dementia in patients with diabetes mellitus. These findings underscore the need for well-controlled large clinical trials and future research in this field.

skandiver: a divergence-based analysis tool for identifying intercellular mobile genetic elements.

Motivation: Mobile genetic elements (MGEs) are as ubiquitous in nature as they are varied in type, ranging from viral insertions to transposons to incorporated plasmids. Horizontal transfer of MGEs across bacterial species may also pose a significant threat to global health due to their capability to harbor antibiotic resistance genes. However, despite cheap and rapid whole-genome sequencing, the varied nature of MGEs makes it difficult to fully characterize them, and existing methods for detecting MGEs often do not agree on what should count. In this manuscript, we first define and argue in favor of a divergence-based characterization of mobile-genetic elements. Results: Using that paradigm, we present skandiver, a tool designed to efficiently detect MGEs from whole-genome assemblies without the need for gene annotation or markers. skandiver determines mobile elements via genome fragmentation, average nucleotide identity (ANI), and divergence time. By building on the scalable skani software for ANI computation, skandiver can query hundreds of complete assemblies against >65 000 representative genomes in a few minutes and 19 GB memory, providing scalable and efficient method for elucidating mobile element profiles in incomplete, uncharacterized genomic sequences. For isolated and integrated large plasmids (>10 kb), skandiver's recall was 48% and 47%, MobileElementFinder was 59% and 17%, and geNomad was 86% and 32%, respectively. For isolated large plasmids, skandiver's recall (48%) is lower than state-of-the-art reference-based methods geNomad (86%) and MobileElementFinder (59%). However, skandiver achieves higher recall on integrated plasmids and, unlike other methods, without comparing against a curated database, making skandiver suitable for discovery of novel MGEs. AVAILABILITY AND IMPLEMENTATION: https://github.com/YoukaiFromAccounting/skandiver.

Floria: fast and accurate strain haplotyping in metagenomes.

SUMMARY: Shotgun metagenomics allows for direct analysis of microbial community genetics, but scalable computational methods for the recovery of bacterial strain genomes from microbiomes remains a key challenge. We introduce Floria, a novel method designed for rapid and accurate recovery of strain haplotypes from short and long-read metagenome sequencing data, based on minimum error correction (MEC) read clustering and a strain-preserving network flow model. Floria can function as a standalone haplotyping method, outputting alleles and reads that co-occur on the same strain, as well as an end-to-end read-to-assembly pipeline (Floria-PL) for strain-level assembly. Benchmarking evaluations on synthetic metagenomes show that Floria is > 3× faster and recovers 21% more strain content than base-level assembly methods (Strainberry) while being over an order of magnitude faster when only phasing is required. Applying Floria to a set of 109 deeply sequenced nanopore metagenomes took <20 min on average per sample and identified several species that have consistent strain heterogeneity. Applying Floria's short-read haplotyping to a longitudinal gut metagenomics dataset revealed a dynamic multi-strain Anaerostipes hadrus community with frequent strain loss and emergence events over 636 days. With Floria, accurate haplotyping of metagenomic datasets takes mere minutes on standard workstations, paving the way for extensive strain-level metagenomic analyses. AVAILABILITY AND IMPLEMENTATION: Floria is available at https://github.com/bluenote-1577/floria, and the Floria-PL pipeline is available at https://github.com/jsgounot/Floria_analysis_workflow along with code for reproducing the benchmarks.

Lipopolysaccharide Triggers Luminal Acidification to Promote Defense Against Bacterial Infection in Vaginal Epithelium.

The vaginal epithelium plays pivotal roles in host defense against pathogen invasion, contributing to the maintenance of an acidic microenvironment within the vaginal lumen through the activity of acid-base transport proteins. However, the precise defense mechanisms of the vaginal epithelium after a bacterial infection remain incompletely understood. This study showed that bacterial lipopolysaccharide (LPS) potentiated net proton efflux by up-regulating the expression of Na+-H+ exchanger 1 (NHE1) without affecting other acid-base transport proteins in vaginal epithelial cells. Pharmacologic inhibition or genetic knockdown of Toll-like receptor-4 and the extracellular signal-regulated protein kinase signaling pathway effectively counteracted the up-regulation of NHE1 and the enhanced proton efflux triggered by LPS in vaginal epithelial cells. In vivo studies revealed that LPS administration led to luminal acidification through the up-regulation of NHE1 expression in the rat vagina. Moreover, inhibition of NHE exhibited an impaired defense against acute bacterial infection in the rat vagina. These findings collectively indicate the active involvement of vaginal epithelial cells in facilitating luminal acidification during acute bacterial infection, offering potential insights into the treatment of bacterial vaginosis.

A systematic review and meta-analysis on the transcriptomic signatures in alcohol use disorder.

Currently available clinical treatments on alcohol use disorder (AUD) exhibit limited efficacy and new druggable targets are required. One promising approach to discover new molecular treatment targets involves the transcriptomic profiling of brain regions within the addiction neurocircuitry, utilizing animal models and postmortem brain tissue from deceased patients with AUD. Unfortunately, such studies suffer from large heterogeneity and small sample sizes. To address these limitations, we conducted a cross-species meta-analysis on transcriptome-wide data obtained from brain tissue of patients with AUD and animal models. We integrated 36 cross-species transcriptome-wide RNA-expression datasets with an alcohol-dependent phenotype vs. controls, following the PRISMA guidelines. In total, we meta-analyzed 964 samples - 502 samples from the prefrontal cortex (PFC), 282 nucleus accumbens (NAc) samples, and 180 from amygdala (AMY). The PFC had the highest number of differentially expressed genes (DEGs) across rodents, monkeys, and humans. Commonly dysregulated DEGs suggest conserved cross-species mechanisms for chronic alcohol consumption/AUD comprising MAPKs as well as STAT, IRF7, and TNF. Furthermore, we identified numerous unique gene sets that might contribute individually to these conserved mechanisms and also suggest novel molecular aspects of AUD. Validation of the transcriptomic alterations on the protein level revealed interesting targets for further investigation. Finally, we identified a combination of DEGs that are commonly regulated across different brain tissues as potential biomarkers for AUD. In summary, we provide a compendium of genes that are assessable via a shiny app, and describe signaling pathways, and physiological and cellular processes that are altered in AUD that require future studies for functional validation.