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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2019

From rare Copy Number Variations to biological processes in ADHD

AimAttention-deficit/hyperactivity disorder (ADHD) is a highly heritable psychiatric disorder. The objective of this study was to define ADHD-associated candidate genes, and their associated molecular modules and biological themes, based on the analysis of rare genetic variants.\n\nMethodsWe combined data from 11 published copy number variation (CNV) studies in 6176 individuals with ADHD and 25026 controls and prioritized genes by applying an integrative strategy based on criteria including recurrence in ADHD individuals, absence in controls, complete coverage in copy number gains, and presence in the minimal region common to overlapping CNVs, as well as on protein-protein interactions and information from cross-species genotype-phenotype annotation.\n\nResultsWe localized 2241 eligible genes in the 1532 reported CNVs, of which we classified 432 as high-priority ADHD candidate genes. The high-priority ADHD candidate genes were significantly co-expressed in the brain. A network of 66 genes was supported by ADHD-relevant phenotypes in the cross-species database. In addition, four significantly interconnected protein modules were found among the high-priority ADHD genes. A total of 26 genes were observed across all applied bioinformatic methods. Look-up in the latest genome-wide association study for ADHD showed that among those 26, POLR3C and RBFOX1 were also supported by common genetic variants.\n\nConclusionsIntegration of a stringent filtering procedure in CNV studies with suitable bioinformatics approaches can identify ADHD candidate genes at increased levels of credibility. Our pipeline provides additional insight in the molecular mechanisms underlying ADHD and allows prioritization of genes for functional validation in validated model organisms.

genetics↗

bioRxiv2019

Defining and targeting adaptations to oncogenic KRASG12C inhibition using quantitative temporal proteomics

Covalent inhibitors of the KRASG12C oncoprotein have recently been developed and are being evaluated in clinical trials. Resistance to targeted therapies is common and likely to limit long-term efficacy of KRAS inhibitors (KRASi). To identify pathways of adaptation to KRASi and to predict drug combinations that circumvent resistance, we used a mass spectrometry-based quantitative temporal proteomics and bioinformatics workflow to profile the temporal proteomic response to KRASG12C inhibition in pancreatic and lung cancer 2D and 3D cellular models. We quantified 10,805 proteins across our datasets, representing the most comprehensive KRASi proteomics effort to date. Our data reveal common mechanisms of acute and long-term response between KRASG12C-driven tumors. To facilitate discovery in the cancer biology community, we generated an interactive KRASi proteome website (https://manciaslab.shinyapps.io/KRASi/). Based on these proteomic data, we identified potent combinations of KRASi with PI3K, HSP90, CDK4/6, and SHP2 inhibitors, in some instances converting a cytostatic response to KRASi monotherapy to a cytotoxic response to combination treatment. Overall, using our quantitative temporal proteomics-bioinformatics platform, we have comprehensively characterized the proteomic adaptations to KRASi and identified combinatorial regimens to induce cytotoxicity with potential therapeutic utility.

cancer biology↗

bioRxiv2019

Leveraging targeted sequencing for non-model species: a step-by-step guide to obtain a reduced SNP set and a pipeline to automate data processing in the Antarctic Midge, Belgica antarctica.

The sequencing of whole or partial (e.g. reduced representation) genomes are commonly employed in molecular ecology and conservation genetics studies. However, due to sequencing costs, a trade-off between the number of samples and genome coverage can hinder research for non-model organisms. Furthermore, the processing of raw sequences requires familiarity with coding and bioinformatic tools that are not always available. Here, we present a guide for isolating a set of short, SNP-containing genomic regions for use with targeted amplicon sequencing protocols. We also present a python pipeline--PypeAmplicon-- that facilitates processing of reads to individual genotypes. We demonstrate the applicability of our method by generating an informative set of amplicons for genotyping of the Antarctic midge, Belgica antarctica, an endemic dipteran species of the Antarctic Peninsula. Our pipeline analyzed raw sequences produced by a combination of high-multiplexed PCR and next-generation sequencing. A total of 38 out of 47 (81%) amplicons designed by our panel were recovered, allowing successful genotyping of 42 out of 55 (76%) targeted SNPs. The sequencing of [~]150 bp around the targeted SNPs also uncovered 80 new SNPs, which complemented our analyses. By comparing overall patterns of genetic diversity and population structure of amplicon data with the low-coverage, whole-genome re-sequencing (lcWGR) data used to isolate the informative amplicons, we were able to demonstrate that amplicon sequencing produces information and results similar to that of lcWGR. Our methods will benefit other research programs where rapid development of population genetic data is needed but yet prevented due to high expense and a lack of bioinformatic experience.

evolutionary biology↗

bioRxiv2019

Genomic characterization and computational phenotyping of nitrogen-fixing bacteria isolated from Colombian sugarcane fields

Previous studies have shown that the sugarcane microbiome harbors diverse plant growth promoting (PGP) microorganisms, including nitrogen-fixing bacteria, and the objective of this study was to design a genome-enabled approach to prioritize sugarcane associated nitrogen-fixing bacteria according to their potential as biofertilizers. Using a systematic high throughput approach, 22 pure cultures of nitrogen-fixing bacteria were isolated and tested for diazotrophic potential by PCR amplification of nitrogenase (nifH) genes, common molecular markers for nitrogen fixation capacity. Genome sequencing confirmed the presence of intact nitrogenase nifH genes and operons in the genomes of 18 of the isolates. Isolate genomes also encoded operons for phosphate solubilization, siderophore production operons, and other PGP phenotypes. Klebsiella pneumoniae strains comprised 14 of the 22 nitrogen-fixing isolates, and four others were members of closely related genera to Klebsiella. A computational phenotyping approach was developed to rapidly screen for strains that have high potential for nitrogen fixation and other PGP phenotypes while showing low risk for virulence and antibiotic resistance. The majority of sugarcane isolates were below a genotypic and phenotypic threshold, showing uniformly low predicted virulence and antibiotic resistance compared to clinical isolates. Six prioritized strains were experimentally evaluated for PGP phenotypes: nitrogen fixation, phosphate solubilization, and the production of siderophores, gibberellic acid and indole acetic acid. Results from the biochemical assays were consistent with the computational phenotype predictions for these isolates. Our results indicate that computational phenotyping is a promising tool for the assessment of benefits and risks associated with bacteria commonly detected in agricultural ecosystems.\n\nIMPORTANCEA genome-enabled approach was developed for the prioritization of native bacterial isolates with the potential to serve as biofertilizers for sugarcane fields in Colombias Cauca Valley. The approach is based on computational phenotyping, which entails predictions related to traits of interest based on bioinformatic analysis of whole genome sequences. Bioinformatic predictions of the presence of plant growth promoting traits were validated with experimental assays and more extensive genome comparisons, thereby demonstrating the utility of computational phenotyping for assessing the benefits and risks posed by bacterial isolates that can be used as biofertilizers. The quantitative approach to computational phenotyping developed here for the discovery of biofertilizers has the potential for use with a broad range of applications in environmental and industrial microbiology, food safety, water quality, and antibiotic resistance studies.

microbiology↗

bioRxiv2019

Functional analysis of phospholipase Dδ family in tobacco pollen tubes

Phosphatidic acid (PA), important signalling and metabolic phospholipid, is predominantly localized in the subapical plasma membrane (PM) of growing pollen tubes. PA can be produced from structural phospholipids by phospholipase D (PLD) but the isoforms responsible for production of plasma membrane PA were not identified yet and their functional roles remain unknown. Following genome-wide bioinformatic analysis of PLD family in tobacco, we focused on the pollen-overrepresented PLD{delta} class. Combining live-cell imaging, gene overexpression or knock-down, lipid-binding and structural bioinformatics, we characterized 5 NtPLD{delta} isoforms. Distinct PLD{delta} isoforms preferentially localize to the cytoplasm or subapical PM. Using fluorescence recovery after photobleaching, domain deletion and swapping analyses we show that membrane-bound PLD{delta}s are tightly bound to PM, primarily via the central catalytic domain. Knock-down, overexpression and in vivo PA level analyses revealed isofom PLD{delta}3 as the most important member of the PLD{delta} subfamily active in pollen tubes. PA promotes binding of PLD{delta}3 to the PM, thus creating a positive feedback loop, where PA accumulation leads to the formation of massive PM invaginations. Tightly controlled production of PA generated by PLD{delta}3 at the PM is important for maintaining the balance between various membrane trafficking processes, that are crucial for plant cell tip growth.

plant biology↗

bioRxiv2019

HIV-1 Rev interacts with HERV-K RcREs present in the human genome and promotes export of unspliced HERV-K proviral RNA

BackgroundThe HERV-K (HML-2) viruses are the youngest of the human endogenous retroviruses. They are present as several almost complete proviral copies and numerous fragments in the human genome. Many HERV-K proviruses express a regulatory protein Rec, which binds to an element present in HERV-K mRNAs called the RcRE. This interaction is necessary for the nucleo-cytoplasmic export and expression of HERV-K mRNAs that retain introns and plays a role analogous to that of Rev and the RRE in HIV replication. There are over 900 HERV-K RcREs distributed throughout the human genome. Thus, it was of interest to determine if Rev could functionally interact with selected RcRE elements that map either to HERV-K proviruses or human gene regions. This interaction would have the potential to alter the expression of both HERV-K mRNAs and cellular mRNAs during HIV-1 infection. ResultsIn this study we employed a combination of RNAseq, bioinformatics and cell-based functional assays. Potential RcREs were identified through a number of bioinformatic approaches. They were then tested for their ability to promote export and translation of a reporter mRNA with a retained intron in conjunction with Rev or Rec. Some of the selected elements functioned well with either Rev, Rec or both, whereas some showed little or no function. Rev function on individual RcREs varied and was also dependent on the Rev sequence. We also performed RNAseq on total and cytoplasmic RNA isolated from SupT1 cells expressing HIV Rev, with or without Tat, or HERV-K Rec. Proviral mRNA from three HERV-K loci (4p16.1b, 22q11.23 and most significantly 3q12.3) accumulated in the cytoplasm in the presence of Rev or Tat and Rev, but not Rec. Consistent with this, the 3 RcRE from 3q12.3 functioned well with HIV-Rev in our reporter assay. In contrast, this RcRE showed little or no function with Rec. ConclusionsThe HIV Rev protein can functionally interact with many RcREs present in the human genome, depending on the RcRE sequence, as well as the Rev sequence. This leads to export of some of the HERV-K proviral mRNAs and also has the potential to change the expression of non-viral genes.

cell biology↗

bioRxiv2019

Distinct microbiome composition of floor and air dust distort richness estimation in university dormitories

The number of culture-independent indoor microbiome study has increased remarkably in recent years, but microbial composition among different sampling strategies remains poorly characterized and their impact to downstream microbiome analysis is also not clear. In this study, we reported a case study of microbial composition of floor and air dust in 87 dormitory rooms of Shanxi University, China. Floor and air dust were collected by vacuum cleaner and petri-dish, respectively, and the bacterial composition was characterized by 16S rRNA sequencing. The composition of floor and air dust differed significantly (R2 = 0.65, p < 0.001, Adonis), and Pseudomonas dominated in floor dust (75.1%) but was less common in air dust (1.9%). The top genera in air dust, including Ralstonia (15.6%), Pelomonas (11.3%), Anoxybacillus (9.3%) and Ochrobactrum (6.2%), all accounted for < 1% abundance in floor dust. The dominant Pseudomonas in floor dust swamped low frequency organisms, leading to significant lower number of operational taxonomic units (OTUs) compared with air dust in the same sequencing depth. The different microbial composition of floor and air dust can lead to differences in downstream bioinformatics analyses. We searched the dormitory microbiome against ~200,000 samples deposited in Microbiome Search Engine (MSE), and found that the compositions of floor dust samples were similar to samples from building environment and human nasopharynx, whereas the compositions of the air dust samples were similar to mosquito tissues. ImportanceIncreasing number of indoor microbiome studies has been conducted in recent years, but the impact of sampling strategy is far from clear. In this study, we reported that the floor and air sampling can lead to drastic variation in microbial composition and downstream analyses in university dormitories, including microbial diversity estimation and compositional similarity search. Thus, the bioinformatics analysis results need to be interpreted with caution in microbiome studies, and it may be necessary to collected samples from different sampling strategies to comprehensively characterize the microbial composition and exposure to human occupants in an indoor environment.

microbiology↗

bioRxiv2019

Increased yields of duplex sequencing data by a series of quality control tools

Duplex sequencing is currently the most reliable method to identify ultra-low frequency DNA variants by grouping sequence reads derived from the same DNA molecule into families with information on the forward and reverse strand. However, only a small proportion of reads are assembled into duplex consensus sequences, and reads with potentially valuable information are discarded at different steps of the bioinformatics pipeline, especially reads without a family. We developed a bioinformatics tool-set that analyses the tag and family composition with the purpose to understand data loss and implement modifications to maximize the data output for the variant calling. Specifically, our tools show that tags contain PCR and sequencing errors that contribute to data loss and lower DCS yields. Our tools also identified chimeras, which result in unpaired families that do not form DCS. Finally, we also developed a tool called Variant Analyzer that re-examines variant calls from raw reads and provides different summary data that categorizes the confidence level of a variant call by a tier-based system. We demonstrate that this tool identified false positive variants tagged by the tier-based classification. Furthermore, with this tool we can include reads without a family and check the reliability of the call, which increases substantially the sequencing depth for variant calling, a particular important advantage for low-input samples or low-coverage regions.

genomics↗

bioRxiv2019

Comprehensive single-PCR 16S and 18S rRNA community analysis validated with mock communities and denoising algorithms

Universal SSU rRNA primers allow comprehensive quantitative profiling of natural communities by simultaneously amplifying templates from Bacteria, Archaea, and Eukaryota in a single PCR reaction. Despite the potential to show all rRNA gene relative gene abundances, they are rarely used due to concerns about length bias against 18S amplicons and bioinformatic challenges converting mixed 16S/18S sequences into amplicon sequence variants. We thus developed 16S and 18S rRNA mock communities and a bioinformatic pipeline to validate this three-domain approach. To test for length biases, we mixed eukaryotic and prokaryotic mocks before PCR, and found consistent two-fold underestimation of longer 18S sequences due to sequencing but not PCR bias. Using these mocks, we show universal V4-V5 primers (515Y/926R) outperformed eukaryote-specific V4 primers in observed vs. expected abundance correlations and sequences with single mismatches to the primer were strongly underestimated (3-8 fold). A year of monthly time-series data from a protist-enriched 1.2-80 m size fraction yielded an average of 9% 18S, 17% chloroplast 16S, and 74% prokaryote 16S rRNA gene amplicons. These data demonstrate the potential for universal primers to generate quantitative and comprehensive microbiome profiles, although gene copy and genome size variability should be considered - as for any quantitative genetic analysis.

microbiology↗

bioRxiv2025

Comparative essentialome analysis of six Pectobacteriaceae strains using the TNSEEK pipeline identifies conserved and strain-specific fitness determinants

Transposon sequencing (Tn-seq) is a powerful technique for defining the essential genes required for bacterial survival. However, gene essentiality can vary significantly across taxonomic levels, and comparing large Tn-seq datasets from multiple strains presents considerable analytical challenges. To address this, we developed TNSEEK, a fully automated bioinformatics pipeline for the systematic and comparative analysis of transposon sequencing experiments. We applied TNSEEK to analyze six Soft Rot Pectobacteriaceae (SRP) strains, encompassing species from the Dickeya and Pectobacterium genera, grown in a rich medium. This approach identified a core essentialome of 225 genes, primarily involved in fundamental cellular maintenance, conserved across all six strains, a set comparable in size to that of the broader Enterobacteriaceae family. Only a few genus-specific essential genes were found highlighting interesting distinct metabolic capabilities between Dickeya and Pectobacterium genera. In striking contrast, we discovered a large variable essentialome comprising 181 strain-specific genes, many of which of unknown function. A portion of these strain-specific essential genes are components of defense systems and prophage genomic regions. The unexpected essentiality of these modules suggests they form a constitutively active frontline defense. Furthermore, a comparison with the E. coli essentialome demonstrates that discrepancies in gene essentiality can often be attributed to differences in growth conditions, particularly temperature, as well as variations in genetic redundancy. In conclusion, the TNSEEK pipeline is a robust tool for exploring functional genomics across multiple strains. IMPORTANCEDickeya and Pectobacterium are two genera of the Pectobacteriaceae family that contain mainly plant pathogenic bacteria. To analyze the diversity within bacteria of this family, we performed a Tn-seq analysis on six strains representing a range of ecological niches. To this aim we developed a bioinformatics pipeline, termed TNSEEK which allows the comparative analysis of results across diverse experimental conditions and multiple strains. Applied to growth in rich medium of the tested strains, it allowed the identification of an essentialome of 225 genes at the family level, few genus-specific essential genes but a large essentialome comprising 181 strain-specific genes, many of which of unknown function. Thus, TNSEEK proved its ability to analyze a large data set coming from different Tn-seq experiments and it offers an unparalleled flexibility in handling any number of strains and experiments.

genomics↗

bioRxiv2025

Identification of SASP-associated biomarkers and regulatory mechanisms in diabetic foot ulcers based on transcriptomics and experimental validation

BackgroundDiabetic foot ulcers (DFU) constitute a major complication arising from diabetes mellitus. Emerging research findings have underscored the pivotal contribution of cellular senescence to the pathophysiological development of wounds exhibiting delayed healing; nevertheless, the molecular regulatory networks governing this process in DFU pathogenesis remain incompletely elucidated MethodsDFU-related transcriptomic datasets were acquired from public databases. Biomarkers were identified through machine learning algorithms combined with expression validation. To evaluate the diagnostic predictive capacity of identified biomarkers for DFU, a nomogram prediction model was developed and validated. Further analyses included Gene Set Enrichment Analysis (GSEA), molecular network regulation, immune infiltration profiling, and drug prediction. Subsequently, the expression profiles of these biomarkers were quantitatively assessed through reverse transcription quantitative PCR (RT-qPCR) methodology. ResultsFour feature genes were identified using machine learning. Among them, CXCR2 and SIGLEC7 passed expression validation and were significantly up-regulated in DFU groups across two datasets (p < 0.05), confirming their potential as biomarkers. A nomogram constructed based on these two biomarkers demonstrated high discriminative accuracy and good calibration (decision curve net benefit > 0, AUC = 0.99). GSEA indicated that CXCR2 and SIGLEC7 were both enriched in the cytokine-cytokine receptor interaction pathway as well as other functionally associated pathways. Molecular regulatory network analysis indicated that both CXCR2 and SIGLEC7 were predicted to be regulated by transcription factors (TFs) such as SOX2. Immune infiltration analysis showed a significant strong positive correlation between CXCR2 and activated mast cells (correlation coefficient (cor) = 0.72, p < 0.001), and between SIGLEC7 and macrophages M0 (cor = 0.71, p < 0.001). Drug prediction identified 12 drugs targeting CXCR2 (e.g., Indoprofen) and one drug targeting SIGLEC7 (N-acetyl-alpha-D-glucosamine). Validation through Reverse Transcription quantitative Polymerase Chain Reaction (RT-qPCR) revealed that CXCR2 and SIGLEC7 expression levels were markedly increased in the DFU group, showing statistically significant differences (p<0.05), which aligned with the bioinformatics analysis outcomes ConclusionThis study identified CXCR2 and SIGLEC7 as SASPRG-related biomarkers in DFU through bioinformatic analysis, providing new theoretical support and a basis for early diagnosis and treatment of DFU.

genomics↗

bioRxiv2025

Chromatin profiling for everyone: FFPE-CUTAC for the theory and practice of modern molecular biology

In 2025, together with the Fred Hutch Summer Undergraduate Research and Summer High School Internship programs, we developed and implemented a laboratory genomics research experience to introduce students to modern molecular biology techniques and bioinformatics. The course centered around using a new method we had developed in 2023 that uses readily available fixed tissue sections on glass slides. Students performed a series of steps to tagment genomic locations of RNA Polymerase II and then used PCR to enrich libraries for next-generation sequencing in a core facility. Students then visualized their data in genomic browser tracks and assessed the results. At the end of the summer, students prepared and presented their work and experiences in seminar format to their cohorts. Overall, the technical simplicity of on-slide chromatin profiling introduced the students to laboratory practice and current techniques in genomics, bioinformatics, and medical sciences.

scientific communication and education↗

bioRxiv2026

EZ-DMS - A Simple and Accessible Protocol and Software Package for Deep Mutational Scanning of Virus Proteins

Mutations that occur during viral genome replication can result in new phenotypes, such as infection of new cell types or resistance to therapeutics. To determine the phenotypic potential of viruses, deep mutational scanning (DMS) can be used. This approach measures the effects of all amino acid changes at sites of interest on protein function, virus infectivity, or resistance to therapeutics. A virus library that contains all possible variants is produced and used to infect a culture of cells. The frequency of each amino acid at the DMS site in the infected culture relative to the input stock captures the relative fitness for each form under the selective pressure applied. Current DMS protocols are complex and costly due to reliance on deep sequencing for genomic characterization. They also require expertise in bioinformatics to process and analyze the data, thus limiting the number of labs that can apply the technology. Here, we describe a simple and efficient protocol to perform DMS on single sites and on two-site combinations in the Env protein of HIV-1. Dual-site DMS allows probing for epistatic effects. The protocol greatly reduces recombination of the proviral genome in transformed bacteria, thus efficiency of the method. Sequencing is performed using Oxford Nanopore technology, and the data are uploaded to a graphical user interface-based platform that calculates the amino acid preferences, which describe the relative fitness of all amino acids under the experimental conditions tested (e.g., under selection pressure of a drug). The protocol does not require expertise in bioinformatics and can be completed in approximately 16 days, with 3-4 days of laboratory activity and 12-13 days of incubation, with considerably lower costs than existing systems.

microbiology↗

bioRxiv2026

Refactored genetic parts for modular assembly of the E. coli MccV type I secretion system used to screen class II microcin candidates from plant-associated bacteria

BackgroundMicrocins are small antibacterial proteins secreted by gram-negative bacteria. The activities of new microcins discovered using bioinformatic searches need to be validated and characterized to understand how they mediate competition in microbiomes and to evaluate their potential as new therapeutics for combating antibiotic resistance. Engineered plasmids containing the type I secretion system associated with Escherichia coli Microcin V (MccV) can secrete heterologous proteins, including other class II microcins, and this system functions in other bacterial hosts. However, existing microcin secretion constructs are not designed for easily swapping components -- such as origins of replication, resistance genes, promoters, and signal peptides -- that may need to be changed for compatibility with other chassis. ResultsWe refactored the E. coli MccV type I secretion system into genetic parts compatible with a modular Golden Gate assembly scheme and used these parts to construct two-plasmid microcin secretion systems. In our design, one plasmid encodes the type I secretion system proteins, and the other encodes a signal peptide fused to the cargo protein that will be secreted. We tested two versions of a system with inducible promoters separately controlling expression of the components on each plasmid. One used plasmids that replicate in E. coli and its close relatives. The other used broad-host-range plasmids. When induced to secrete MccV, both versions produced similar zones of inhibition against a susceptible strain of E. coli. Next, we identified putative class II microcins in genomes of bacteria from plant-associated genera (Pantoea, Erwinia, and Xanthomonas) using an existing bioinformatics pipeline. We screened 23 of these putative microcins for E. coli self-inhibition. Seven exhibited some inhibition, mostly later in growth curves, but none had effects that were comparable in strength to MccV. ConclusionsThe genetic parts we created can be assembled in various combinations into tailored systems for secreting small proteins from diverse bacterial chassis. These systems can be used to further characterize the targets of novel microcins and to secrete these or other small proteins for various applications. For example, beneficial bacteria used in crop protection could be engineered to secrete microcins that kill or inhibit plant pathogens to increase their efficacy.

synthetic biology↗

bioRxiv2026

Genomic Characterization of 30 Lytic Klebsiella pneumoniae Bacteriophages

The spread and rise of antimicrobial resistance poses a risk to public health due to limited effective treatment options. Alternative antimicrobials that are effective against gram-negative multi-drug resistant pathogens. The increasing rate of carbapenem resistance observed in Klebsiella pneumoniae, indicates the need for alternative antimicrobial options. Bacteriophages that target Klebsiella pneumoniae are promising alternative antimicrobial option, with successful treatments being reported. Here we characterized 30 lytic bacteriophages from various environmental sources and tested their effectiveness against nine clinically relevant carbapenem-resistant K. pneumoniae isolates. These phages were characterized through genomic sequencing, bioinformatic analysis, virulence in liquid medium, and host range on different mediums. Bioinformatic analysis revealed a diverse collection of phages that span 9 ICTV recognized families and 13 genera with genome sizes ranging from 39-349 kbp. The phages were able to inhibit bacterial growth, and no virulence or antibiotic resistance genes were detected within the phage genomes. Host range testing demonstrated phages with broad host range have varying infectivity when plated on different common growth mediums. This study includes candidate phages for further potential development as potential antimicrobial agents against CR-KP, and the complexity in understanding phage-host dynamics of non-capsule phages that target against K. pneumoniae.

microbiology↗

bioRxiv2026

Life, the universe, and everything for $42: ultra-low pass sequencing of maize for genotyping, mapping, and pedigree analysis

Convenient and economical genotyping methods and simplified bioinformatic workflows are critical for genetic studies and breeding. The declining cost of sequencing library construction, sample multiplexing, and the advent of skim sequencing has reduced costs and enabled large-scale genetic and genomic experiments. Here, we present a simple skim sequencing and bioinformatics pipeline sufficient for various genotyping applications. Our low-depth skim sequencing method costs 21 USD per sample and provides an average of 144k reads. Our approach uses a double-stranded DNA sample to prepare libraries for genome sequencing. We demonstrate various uses for this strategy in maize, a complex and large (2.5 Gbp) genome. DNA from multiple pedigreed populations, including advanced backcrossed progenies, bi-parental populations, near-isogenic lines, and recombinant inbred lines, were used to map loci, detect donor introgressions, and determine introgression haplotypes. Read counts at known polymorphic positions detected donor genotypes even when derived from parents of unknown origin and could localize mutations of phenotypic impact via bulked segregant analysis. Remarkably, the small amount of sequencing data produced were sufficient to identify the haplotypes of introgressions of unknown origin from by comparison to known genotypes. Correct haplotype identification enabled more accurate allele frequencies to be calculated when mapping loci. This is of exceptional value in maize, where a rich collection of mutants from the 20th century are of unknown pedigree. One sentence summaryEconomical and efficient whole genome ultra-low pass sequencing of DNA samples for numerous genetic and genomic applications.

genetics↗

bioRxiv2026

Structural and evolutionary insights into DAF-12 interactions with transcriptional coactivators in parasitic nematodes

Parasitic nematodes infect billions of humans and livestock worldwide, causing major health and economic burdens, while the spread of anthelmintic resistance threatens current control strategies. A critical step in parasite infection is the resumption of development of infective third-stage larvae (iL3) upon host entry, a process controlled by the nuclear receptor DAF-12. Activation of DAF-12 by dafachronic acids promotes developmental progression and reproductive maturation, making this receptor an attractive therapeutic target. However, the molecular mechanisms governing DAF-12 activation, particularly transcriptional coactivator recruitment, remain poorly understood. Here, we combined biophysical, cellular, structural, and bioinformatic approaches to investigate coactivator recognition by DAF-12 from the parasitic nematodes Brugia malayi and Haemonchus contortus. Crystal structures of ligand-bound DAF-12 ligand-binding domains in complex with coactivator-derived peptides reveal conserved features of ligand-dependent coactivator recruitment shared with mammalian nuclear receptors. In addition, we uncover previously unrecognized interaction features, including motif-specific contacts that extend beyond the canonical LXXLL binding mode of coactivators and distinct patterns of DAF-12 conservation across nematode clades. Structure-guided analyses redefine the interaction motif of the only described parasite-specific coactivator DIP-1 and suggest novel candidate motifs for DAF-12-interacting proteins. Together, these findings establish the structural basis of coactivator binding to nematode DAF-12 and provide mechanistic insight into the transcriptional regulation underlying parasite development. These results expand current understanding of nuclear receptor signaling in parasitic nematodes and provide a framework for the future design of strategies aimed at disrupting DAF-12 activation as a potential antiparasitic approach. Author SummaryParasitic nematodes infect billions of people and livestock worldwide, causing major health and economic burdens, while increasing resistance threatens current treatments. These parasites rely on a developmental switch that allows infectious larvae to resume growth inside their host, a process controlled by the nuclear receptor DAF-12. Blocking this pathway could prevent parasites from establishing infection. However, the molecular mechanisms regulating DAF-12 activation remain poorly understood. Here, we investigate how DAF-12 from two parasitic nematodes, Brugia malayi and Haemonchus contortus, interacts with transcriptional coactivators that enable gene activation, using a combination of biophysical, cellular, structural, and bioinformatic approaches. We identified conserved features of ligand-dependent coactivator recruitment shared with mammalian nuclear receptors as well as nematode-specific interaction mechanisms that vary across evolutionary clades. These findings provide new insights into the structural basis of coactivator binding to DAF-12 and advance our understanding of a key pathway controlling parasitic nematode development.

biochemistry↗

bioRxiv2026

Assessment of Oxford Nanopore whole genome sequencing for large-scale genomic characterisation of Staphylococcus aureus

Whole-genome sequencing (WGS) is increasingly being utilised in microbial diagnostics, surveillance, and research. In this paper we assess the performance of one leading long-read sequencing technology, Oxford Nanopore Technology (ONT), on 836 Staphylococcus aureus bacteraemia isolates. We compare the results to that of a leading short-read sequencing technology, Illumina. All isolates were sequenced using ONT MinION Mk1B and Illumina HiSeq or MiSeq. Libraries were prepared according to manufacturers instructions. Preprocessing and downstream bioinformatic analyses were performed using a combination of in-house pipelines and publicly available software tools. The average base substitution error rate in ONT assemblies was low but varied between sequence types, possibly due to lineage-specific methylation patterns. Multi locus sequence typing was similar between the technologies, while ONT assemblies allowed for better spa typing than Illumina assemblies. The reported detection rate was similar between ONT and Illumina assemblies for most virulence- and AMR-associated genes and variants. For 42 (22.2%) of 189 genes/variants, the two technologies disagreed in gene detection in 5 isolates or more, and in 39 (20.6.%) of these the highest detection rate was found with ONT. Discrepancies were mainly associated with low GC content, multiple repetitive segments, and small plasmids. Polishing of ONT data resulted in minor changes in gene/variant calling. Our study supports the use of ONT WGS for bacterial population genomic studies on a large collection of S. aureus isolates. While assembly of ONT reads may be affected by its own methodological limitations, it was superior to Illumina assemblies in detection of potentially clinically relevant genes and variants at a low read error rate. Understanding the advantages and limitations of WGS technologies is essential before undertaking studies involving such methods on large sets of bacteria. Author summaryIn this paper, we present a practical assessment of one important whole genome sequencing (WGS) method, Oxford Nanopore Technology (ONT), and compare its performance in bacterial population genomics to that of WGS with Illumina technology. Our goal was to investigate the usefulness of ONT in studies aiming to identify clinically relevant bacterial characteristics in large collections of bacteria, such as genotype-phenotype studies. We sequenced a large set of clinical S. aureus isolates from episodes of bloodstream infections using both ONT and Illumina technologies and performed analyses with widely used software and bioinformatic pipelines. We have elucidated inherent strengths and limitations of ONT and Illumina sequencing and report some of the practical consequences of these on bacterial typing and detection of clinically relevant genes. With this study, we present one of the most comprehensive assessments of long-read sequencing technology for the genomic characterisation of clinical bacterial isolates, and the findings provide guidance for researchers considering WGS in large-scale bacterial genomics.

genomics↗