Biology subjects

Wheeler, T.

Publications and source records attributed to Wheeler, T..

15 recordsLinked to original sources

bioRxiv2026

Temperature-sensitive cytoplasmic incompatibility across divergent Wolbachia partly reflects cifB transcription, not endosymbiont density

Maternally transmitted Wolbachia bacteria are common in insects, with many strains altering host reproduction through cytoplasmic incompatibility (CI). CI kills embryos fertilized by Wolbachia-bearing males unless those embryos also carry Wolbachia, which favors females with Wolbachia and drives the endosymbiont to higher frequencies in host populations. Strong CI now underpins successful applications that rely on maintaining pathogen-blocking Wolbachia transinfections in vector populations to reduce arboviral disease transmission. Temperature modulates CI strength (the proportion of embryos killed), with consequences for Wolbachia prevalence in natural and transinfected populations. Yet the mechanisms regulating temperature-sensitive CI-strength variation are poorly understood. We quantified CI strength across eight divergent Drosophila-associated Wolbachia strains at four temperatures (18{degrees}C-26{degrees}C), while characterizing development time, Wolbachia and Wovirus densities, and transcription of the CI-inducing gene cifB. Four of eight Wolbachia strains exhibited temperature-sensitive CI, three of which induced CI at multiple temperatures. Of these three, two expressed significantly more cifB at the temperature yielding stronger CI, whereas testes Wolbachia density did not predict CI strength. Notably, cifB-transcript levels were consistently decoupled from Wolbachia and Wovirus densities, suggesting that cifB transcription is not regulated solely by symbiont abundance. We also report temperature-sensitive rescue of CI, Wolbachia-associated developmental acceleration, and strain-specific Wovirus-Wolbachia covariance. Our findings reveal temperature as a pervasive modulator of Wolbachia-host interactions at multiple levels and extend evidence that cifB transcription partly predicts variable CI strength across strain identities, male ages, and now temperatures. CI variation unaccounted for by cifB transcription points toward additional regulatory or post-transcriptional mechanisms that we discuss.

molecular biology↗

bioRxiv2026

Rational reduction of a sorghum SynCom that preserves growth promotion reveals flavonoid-mediated plant microbe interactions

O_LIPlant growth is influenced by the composition of its associated microbiome. The inherent complexity and functional redundancy of natural plant microbiomes presents a formidable barrier to understanding the myriad biological interactions therein. Efforts have been made to develop synthetic microbial communities (SynComs) that can provide a rigorous and generalizable framework for the rational design of next-generation microbial products for sustainable agriculture. We test multiple strategies for stable, plant growth promoting SynCom design and evaluate the phenotypic and molecular impacts of a successful plant-SynCom interaction. C_LIO_LIWe designed 4 distinct, reduced-complexity variants of SynCom SRC1 and assessed their capacities for colonization, stability, and plant growth promotion. To understand the impact on plant performance of our highest performing SynCom variant, we characterized the hosts longitudinal transcriptional response to SynCom inoculation and corroborated the results with metabolomics analysis. C_LIO_LIThe top performing SynCom stably colonized sorghum roots and rhizospheres, elicited plant growth promotion, and induced dynamic spatiotemporal gene transcription in sorghum roots and shoots defined by modulation of growth-defense tradeoff machinery and enhanced flavonoid production. C_LIO_LIThe resultant reduced-complexity SynCom is a highly stable, soil-independent, plant growth promoting, and demonstrates the utility of colonization-based selection criteria, integrated with longitudinal transcriptomic and metabolomic characterization. C_LI

plant biology↗

bioRxiv2025

DIPLOMAT: multi-animal tracking with efficient manual editing

Recent advances in computer vision have enabled the development of automated animal behavior observation tools. Several software packages currently exist for concurrently tracking pose in multiple animals; however, existing tools still face challenges in maintaining animal identities across frames and can demand extensive human oversight and editing. Here we report on DIPLOMAT, a Deep learning-based, Identity-Preserving, Labeled-Object Multi-Animal Tracker, which implements automated algorithms improving tolerance to occlusion and continuity of animal identity over a video, further supplemented by an efficient human interface to help eliminate remaining errors. DIPLOMAT is designed to perform multi-animal tracking by building on the per-frame pose prediction models of two state-of-the-art tools, DeepLabCut and SLEAP. Where other tools immediately take a maximum likelihood estimate from a given video frame, DIPLOMAT splits the probability fields according to the number of tracked animals and then applies an inference method that takes into account across-frame movement and probabilistic distances between body parts. These independent trace probabilities are then preserved for human editing, enabling multiple body parts to be re-tracked across frames with minimal user action. Testing with a standardized and independently tracked dataset of 3-mouse videos shows DIPLOMAT's automated components alone can reduce identity swaps by >75\%. DIPLOMAT code and documentation are available at https://diplomattrack.org/

animal behavior and cognition↗

bioRxiv2024

Activation of three targets by a TAL effector confers susceptibility to bacterial blight of cotton

Xanthomonas spp. employ transcription activator-like effectors (TALEs) to promote pathogenicity by activating host susceptibility (S) genes. Cotton GhSWEET10 is an S gene targeted by a TALE in an early isolate of Xanthomonas citri pv. malvacearum (Xcm), but not by recent field Xcm isolates. To understand the pathogenicity shift in Xcm and its adaptation to cotton, we assembled the whole genome and the TALE repertoire of three recent Xcm Texas field isolates. A newly evolved TALE, Tal7b, activated different GhSWEET genes, GhSWEET14a and GhSWEET14b. Simultaneous activation of GhSWEET14a and GhSWEET14b resulted in pronounced water-soaked lesions. Transcriptome profiling coupled with TALE-binding element prediction identified a pectin lyase as an additional Tal7b target, quantitatively contributing to Xcm virulence alongside GhSWEET14a/b. CRISPR-Cas9-based gene editing supported the function of GhSWEETs as S genes in cotton bacterial blight and the promise of disrupting the TALE-binding site in these genes to control the disease. Collectively, our findings elucidate the rapid evolution of TALEs in Xanthomonas field isolates and highlight the virulence mechanism wherein TALEs induce multiple S genes simultaneously to promote pathogenicity.

plant biology↗

bioRxiv2024

Diviner uncovers hundreds of novel human (and other) exons though comparative analysis of proteins

BackgroundEukaryotic genes are often composed of multiple exons that are stitched together by splicing out the intervening introns. These exons may be conditionally joined in different combinations to produce a collection of related, but distinct, mRNA transcripts. For protein-coding genes, these products of alternative splicing lead to production of related protein variants (isoforms) of a gene. Complete labeling of the protein-coding content of a eukaryotic genome requires discovery of mRNA encoding all isoforms, but it is impractical to enumerate all possible combinations of tissue, developmental stage, and environmental context; as a result, many true exons go unlabeled in genome annotations. ResultsOne way to address the combinatoric challenge of finding all isoforms in a single organism A is to leverage sequencing efforts for other organisms - each time a new organism is sequenced, it may be under a new combination of conditions, so that a previously unobserved isoform may be sequenced. We present Diviner, a software tool that identifies previously undocumented exons in organisms by comparing isoforms across species. We demonstrate Diviners utility by locating hundreds of novel exons in the genomes of human, mouse, and rat, as well as in the ferret genome. Further, we provide analyses supporting the notion that most of the new exons reported by Diviner are likely to be part of a true (but unobserved) isoform of the containing species.

bioinformatics↗

bioRxiv2024

NEAR: Neural Embeddings for Amino acid Relationships

Protein language models (PLMs) have recently demonstrated potential to supplant classical protein database search methods based on sequence alignment, but are slower than common alignment-based tools and appear to be prone to a high rate of false labeling. Here, we present NEAR, a method based on neural representation learning that is designed to improve both speed and accuracy of search for likely homologs in a large protein sequence database. NEARs ResNet embedding model is trained using contrastive learning guided by trusted sequence alignments. It computes per-residue embeddings for target and query protein sequences, and identifies alignment candidates with a pipeline consisting of residue-level k-NN search and a simple neighbor aggregation scheme. Tests on a benchmark consisting of trusted remote homologs and randomly shuffled decoy sequences reveal that NEAR substantially improves accuracy relative to state-of-the-art PLMs, with lower memory requirements and faster embedding and search speed. While these results suggest that the NEAR model may be useful for standalone homology detection with increased sensitivity over standard alignment-based methods, in this manuscript we focus on a more straightforward analysis of the models value as a high-speed pre-filter for sensitive annotation. In that context, NEAR is at least 5x faster than the pre-filter currently used in the widely-used profile hidden Markov model (pHMM) search tool HMMER3, and also outperforms the pre-filter used in our fast pHMM tool, nail.

bioinformatics↗

bioRxiv2024

Sensitive and error-tolerant annotation of protein-coding DNA with BATH

We present BATH, a tool for highly sensitive annotation of protein-coding DNA based on direct alignment of that DNA to a database of protein sequences or profile hidden Markov models (pHMMs). BATH is built on top of the HMMER3 code base, and simplifies the annotation workflow for pHMM-based annotation by providing a straightforward input interface and easy-to-interpret output. BATH also introduces novel frameshift-aware algorithms to detect frameshift-inducing nucleotide insertions and deletions (indels). BATH matches the accuracy of HM-MER3 for annotation of sequences containing no errors, and produces superior accuracy to all tested tools for annotation of sequences containing nucleotide indels. These results suggest that BATH should be used when high annotation sensitivity is required, particularly when frameshift errors are expected to interrupt protein-coding regions, as is true with long read sequencing data and in the context of pseudogenes.

bioinformatics↗

bioRxiv2023

An FPGA-based hardware accelerator supporting sensitivesequence homology filtering with profile hidden Markovmodels

BackgroundSequence alignment lies at the heart of genome sequence annotation. While the BLAST suite of alignment tools has long held an important role in alignment-based sequence database search, greater sensitivity is achieved through the use of profile hidden Markov models (pHMMs). The Forward algorithm that provides much of pHMMs sensitivity is relatively slow, motivating extensive efforts to increase speed. Numerous researchers have devised methods to improve pHMM alignment speed using hardware accelerators such as graphics processing units (GPUs) and field programmable gate arrays (FPGAs). Here, we describe an FPGA hardware accelerator for a key bottleneck step in the analysis pipeline employed by the popular pHMM aligment tool, HMMER. HMMER accelerates pHMM Forward alignment by screening most sequence with a series of filters that rapidly approximate the result of computing full Forward alignment. The first of these filters, the Single Segment ungapped Viterbi (SSV) algorithm, is designed to filter out 98% of non-related inputs and accounts for 70% of the overall runtime of the DNA search tool nhmmer in common use cases. SSV is an ideal target for hardware acceleration due to its limited data dependency structure. ResultsWe present Hardware Accelerated single segment Viterbi Additional Coprocessor (HAVAC), an FPGA-based hardware accelerator for the SSV algorithm. The core HAVAC kernel calculates the SSV matrix at 1739 GCUPS on a Xilinx Alveo U50 FPGA accelerator card, [~] 227x faster than the optimized SSV implementation in nhmmer. Accounting for PCI-e data transfer data processing, HAVAC is 65x faster than nhmmers SSV with one thread and 35x faster than nhmmer with four threads, and uses [~] 31% the energy of a traditional high end Intel CPU. Because these computations are performed on a co-processor, the host CPU remain free to simultaneously compute downstream pHMM alignment and later post-processing. Author summarySequence alignment lies at the heart of genome sequence annotation, and must be both fast and accurate. Signals of relationships between sequences are obscured over time by mutational forces, so that alignment and annotation of the full diversity of life demands highly sensitive tools. Profile hidden Markov models (pHMMs) provide the greatest sensitivity in the face of diversity, but are relatively slow. Here, we describe an approach to improving the speed of pHMM search that leverages field programmable gate arrays - hardware devices that can be configured to implement arbitrary digital circuits to achieve impressive parallelism and energy efficiency. Our tool, HAVAC, accelerates one key bottleneck step in the analysis pipeline employed by the popular pHMM aligment tool, HMMER. HAVAC produces a [~] 60x speedup over the analogous stage in HMMER. HAVAC can be implemented as a part of a larger sequence homology search tool for faster search times and reduced energy usage. Interested users can download HAVAC on github at https://github.com/TravisWheelerLab/HAVAC.

bioinformatics↗

bioRxiv2023

Targeted development of diagnostic SNP markers for resistance to Fusarium wilt race 4 in Upland cotton (Gossypium hirsutum)

Fusarium wilt caused by the soil-borne fungus Fusarium oxysporum f. sp. vasinfectum (FOV) race 4 (FOV4) has become one of the most important emerging diseases in US cotton production. Numerous QTLs have been reported for resistance to FOV; however, no major FOV4-resistance QTL or gene has been identified and used in breeding Upland cotton (Gossypium hirsutum) for FOV4 resistance. In this study, a panel of 223 Chinese Upland cotton accessions was evaluated for FOV4 resistance based on seedling mortality rate (MR) and stem and root vascular discoloration (SVD and RVD). SNP markers were developed based on targeted genome sequencing using AgriPlex Genomics. The chromosome region at 2.130-2.292 Mb on D03 was significantly correlated with both SVD and RVD but not with MR. Based on the two most significant SNP markers, accessions homozygous for AA or TT SNP genotype averaged significantly lower SVD (0.88 vs. 2.54) and RVD (1.46 vs. 3.02) than those homozygous for CC or GG SNP genotype. The results suggested that a gene or genes within the region conferred resistance to vascular discoloration caused by FOV4. The Chinese Upland accessions had 37.22% homozygous AA or TT SNP genotype and 11.66% heterozygous AC or TG SNP genotype, while 32 US elite public breeding lines all had the CC or GG SNP genotype. Among 463 obsolete US Upland accessions, only 0.86% possessed the AA or TT SNP genotype. This study, for the first time, has developed diagnostic SNPs for marker-assisted selection and identified FOV4-resistant Upland germplasms with the SNPs.

plant biology↗

bioRxiv2022

MetaPredict: A machine learning-based tool for predicting metabolic modules in incomplete bacterial genomes

The reconstruction of complete microbial metabolic pathways using omics data from environmental samples remains challenging. Computational pipelines for pathway reconstruction that utilize machine learning methods to predict the presence or absence of KEGG modules in incomplete genomes are lacking. Here, we present MetaPathPredict, a software tool that incorporates machine learning models to predict the presence of complete KEGG modules within bacterial genomic datasets. Using gene annotation data and information from KEGG module databases, MetaPathPredict employs neural network and XGBoost stacked ensemble models to reconstruct and predict the presence of KEGG modules in a genome. MetaPathPredict can be used as a command line tool or as an R package, and both options are designed to be run locally or on a compute cluster. In our benchmarks, MetaPathPredict makes robust predictions of KEGG module presence within highly incomplete genomes.

bioinformatics↗

bioRxiv2022

Molecular fingerprints are not useful in large-scale search for similarly active compounds

Computational approaches for small-molecule drug discovery now regularly scale to consideration of libraries containing billions of candidate small molecules. One promising approach to increased speed in evaluating billion-molecule libraries is to develop succinct representations of each molecule that enable rapid identification of molecules with similar properties. Molecular fingerprints are thought to provide a mechanism for producing such representations. Here, we explore the utility of commonly-used fingerprints in the context of predicting similar molecular activity. We show that fingerprint similarity provides little discriminative power between active and inactive molecules for a target protein based on a known active - while they may sometimes provide some enrichment for active molecules in a drug screen, a screened dataset will still be dominated by inactive molecules. We also demonstrate that high-similarity actives appear to share a scaffold with the query active, meaning that they could more easily be identified by structural enumeration. Furthermore, even when limited to only active molecules, fingerprint similarity values do not correlate with compound potency. In sum, these results highlight the need for a new wave of molecular representations that will improve the capacity to detect biologically active molecules based on similarity to other such molecules.

pharmacology and toxicology↗

bioRxiv2022

Ablation of colonic epithelial Reg4+ support cells induces Notch-independent regeneration and mesenchymal remodeling.

The colonic epithelium harbors a complex network of adult stem cells that integrate signals from many supporting cells to assist in their decision making. In this study, we ablate an epithelial secretory support cell population characterized by Reg4 expression, to investigate the systemic impact on stemness-related cell signaling pathways. Ablation of these cells results in a hyperproliferative state as well as paradoxical activation of Notch signaling, with the proliferative effect continuing even during Notch inhibition. Reg4+ cell ablation also causes an unexpected remodeling of the mesenchyme. We observe increased presence of Pdgfra-high fibroblasts and an expanded network of smooth muscle myofibroblasts, suggesting that Reg4-ablation reorganizes signaling between epithelium and mesenchyme. These changes occur in the absence of any significant immunological inflammatory response. Our data demonstrate that Reg4+ cells are critical directors of homeostatic epithelial-mesenchymal signaling. Further, this ablation model is an in vivo system for probing cell-cell interactions in the colonic stem cell niche. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/478243v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@14ae224org.highwire.dtl.DTLVardef@144e18aorg.highwire.dtl.DTLVardef@13353aeorg.highwire.dtl.DTLVardef@badec4_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2021

From telomere to telomere: the transcriptional and epigenetic state of human repeat elements

Mobile elements and highly repetitive genomic regions are potent sources of lineage-specific genomic innovation and fingerprint individual genomes. Comprehensive analyses of large, composite or arrayed repeat elements and those found in more complex regions of the genome require a complete, linear genome assembly. Here we present the first de novo repeat discovery and annotation of a complete human reference genome, T2T-CHM13v1.0. We identified novel satellite arrays, expanded the catalog of variants and families for known repeats and mobile elements, characterized new classes of complex, composite repeats, and provided comprehensive annotations of retroelement transduction events. Utilizing PRO-seq to detect nascent transcription and nanopore sequencing to delineate CpG methylation profiles, we defined the structure of transcriptionally active retroelements in humans, including for the first time those found in centromeres. Together, these data provide expanded insight into the diversity, distribution and evolution of repetitive regions that have shaped the human genome.

genomics↗

bioRxiv2018

The three dimensional structure of Bovine Salivary Protein 30b (BSP30b) and its interaction with specific rumen bacteria

Bovine Salivary Protein 30b (BSP30b) is a member of the tubular lipid-binding (TULIP) superfamily that includes the human bactericidal/permeability-increasing proteins (BPI), lipopolysaccharide binding proteins (LBP) and palate, lung, and nasal epithelium carcinoma-21 associated proteins (PLUNC). BSP30b is most closely related to the PLUNC family and is predominantly found in bovine saliva. There are four BSP30 isoforms (BSP30a-d) and collectively, they are the most abundant protein component of bovine saliva. The PLUNC family members are proposed to be lipid binding proteins, although in most cases their lipid ligands are unknown. Here, we present the X-ray crystal structure of BSP30b at 2.0 [A] resolution. We used a double methionine mutant and Se-Met SAD phasing to solve the structure. The structure adopts a curved cylindrical form with a hydrophobic channel formed by an /{beta} wrap, which is consistent with the TULIP superfamily. The structure of BSP30b in complex with oleic acid is also presented where the ligand is accommodated within the hydrophobic channel. The electron density for oleic acid suggests that the ligand is only partially occupied in the binding site implying that oleic acid may not be the preferred ligand. GFP-tagged BSP30b binds to the surface of olive oil droplets, as observed under fluorescent microscopy, and acts as a surfactant consistent with its association with decreased susceptibility to bloat in cattle. Bacteria extracted directly from bovine rumen contents indicate that the GFP_BSP30b fusion protein binds to a small number of selected bacterial species in vivo. These results suggest that BSP30b may bind to bacterial lipids from specific species and that this abundant protein may have important biological roles via interacting with rumen bacteria during feeding and rumination.

biochemistry↗

bioRxiv2017

Genomics-enabled analysis of the emergent disease cotton bacterial blight

Cotton bacterial blight (CBB), an important disease of (Gossypium hirsutum) in the early 20th century, had been controlled by resistant germplasm for over half a century. Recently, CBB re-emerged as an agronomic problem in the United States. Here, we report analysis of cotton variety planting statistics that indicate a steady increase in the percentage of susceptible cotton varieties grown each year since 2009. Phylogenetic analysis revealed that strains from the current outbreak cluster with race 18 Xanthomonas citri pv. malvacearum (Xcm) strains.\n\nIllumina based draft genomes were generated for thirteen Xcm isolates and analyzed along with 4 previously published Xcm genomes. These genomes encode 24 conserved and nine variable type three effectors. Strains in the race 18 clade contain 3 to 5 more effectors than other Xcm strains. SMRT sequencing of two geographically and temporally diverse strains of Xcm yielded circular chromosomes and accompanying plasmids. These genomes encode eight and thirteen distinct transcription activator-like effector genes. RNA-sequencing revealed 52 genes induced within two cotton cultivars by both tested Xcm strains. This gene list includes a homeologous pair of genes, with homology to the known susceptibility gene, MLO. In contrast, the two strains of Xcm induce different clade III SWEET sugar transporters. Subsequent genome wide analysis revealed patterns in the overall expression of homeologous gene pairs in cotton after inoculation by Xcm. These data reveal host-pathogen specificity at the genetic level and strategies for future development of resistant cultivars.\n\nAuthor SummaryCotton bacterial blight (CBB), caused by Xanthomonas citri pv. malvacearum (Xcm), significantly limited cotton yields in the early 20th century but has been controlled by classical resistance genes for more than 50 years. In 2011, the pathogen re-emerged with a vengeance. In this study, we compare diverse pathogen isolates and cotton varieties to further understand the virulence mechanisms employed by Xcm and to identify promising resistance strategies. We generate fully contiguous genome assemblies for two diverse Xcm strains and identify pathogen proteins used to modulate host transcription and promote susceptibility. RNA-Sequencing of infected cotton reveals novel putative gene targets for the development of durable Xcm resistance. Together, the data presented reveal contributing factors for CBB re-emergence in the U.S. and highlight several promising routes towards the development of durable resistance including classical resistance genes and potential manipulation of susceptibility targets.

plant biology↗