Biology subjects

Waltari, E.

Publications and source records attributed to Waltari, E..

9 recordsLinked to original sources

bioRxiv2026

RNAquarium: an archive-scale atlas of zebrafish gene expression coupled with pan-taxonomic profiling reveals diverse viral drivers of transcriptomic states

Zebrafish RNA-seq studies span diverse developmental, physiological, and disease contexts, yet most analyses remain confined to individual experiments and disregard the non-zebrafish component of the data. We present RNAquarium, a scalable framework for joint transcriptomic and metatranscriptomic analysis of RNA-seq data and apply it to all publicly available zebrafish RNA-seq datasets in the Sequence Read Archive. This resource captures transcriptomic structure across development and tissues, reveals diverse microbial and viral associations, and identifies previously undescribed zebrafish viruses including a close relative of human influenza B virus linked to distinct host transcriptional states. We further demonstrate that archive-scale transcriptomes can support foundation-model training and prediction of infection-associated transcriptomic signatures. RNAquarium provides an open framework and interactive portal for exploring the breadth of zebrafish gene expression patterns and associated taxa profiled across a large re-search community and establishes a generalizable strategy for integrating transcriptomic and metatranscriptomic analyses across the diversity of life represented in public sequencing archives.

genomics↗

bioRxiv2024

Discovery of a novel bandavirus using metagenomic sequencing in a retrospective analysis of an unresolved 2020 mortality event involving black vultures in the northeastern United States.

Investigations of wildlife diseases and mortality events can sometimes lead to inconclusive results due to limitations in diagnostics combined with an ever-increasing number of emerging viruses. The use of tools such as unbiased metagenomic next generation sequencing (mNGS) can facilitate the identification of causative agents where conventional investigation methods fail. We performed a retrospective mNGS analysis on RNA isolated from postmortem samples collected during a black vulture (Coragyps atratus, family: Cathartidae) mortality event that occurred in eastern Pennsylvania and western New Jersey in 2020. We describe the discovery and identification of a novel species of bandavirus (Phenuiviridae family) in case specimens from this die-off, as well as some of the associated pathological findings. The Bandavirus genus comprises tickborne viral species that have been reported across five continents and implicated in outbreaks in a variety of mammalian hosts, including humans, and in avian species making them important potential sources of zoonotic spillover events. Genomic and phylogenetic analysis of the bandavirus detected in this study indicate its closest relative corresponds to Hunter Island virus, a bandavirus previously implicated in albatross mortality events off the coast of Tasmania, Australia. Follow-up PCR testing of samples from additional vultures from the same cohort confirmed that this new bandavirus is the likely cause of death.

genomics↗

bioRxiv2023

Evolutionary genomics identifies host-directed therapeutics to treat intracellular bacterial infections

Obligate intracellular bacteria shed essential biosynthetic pathways during their evolution towards host dependency, providing an opportunity for host-directed therapeutics. Using Rickettsiaceae as a model, we employed a novel computational pipeline called PoMeLo to systematically compare this cytosolic family of bacteria to the related Anaplasmataceae, which reside in a membrane-bound vacuole in the host cell. We identified 20 metabolic pathways that have been lost since the divergence of Anaplasmataceae and Rickettsiaceae, corresponding to the latters change to a cytosolic niche. We hypothesized that drug inhibition of these host metabolic pathways would reduce the levels of metabolites available to the bacteria, thereby inhibiting bacterial growth. We tested 22 commercially available inhibitors for 14 of the identified pathways and found that the majority (59%) reduced bacterial growth at concentrations that did not induce host cell cytotoxicity. Of these, 5 inhibitors with an IC50 under 5 M were tested to determine whether their mode of inhibition was bactericidal or bacteriostatic. Both mycophenolate mofetil, an inhibitor of inosine-5-monophosphate dehydrogenase in the purine biosynthesis pathway, and roseoflavin, an analog of riboflavin, displayed bactericidal activity. A complementary unbiased mass spectrometry-based metabolomics approach identified 14 pathways impacted by Rickettsia infection based on alterations in metabolite levels. Strikingly, 11 of these (79%) overlapped with those identified by our computational predictions. These in vitro validation studies support the feasibility of a novel evolutionary genomics-guided approach for host-directed antibiotic drug development against obligate pathogens. ImportanceMany pathogens have evolved to acquire essential metabolites from their host cell, while in turn shedding their own biosynthetic capacities. This leads to an interesting dilemma: on one hand, reduced genomes allow pathogens to save energy and replicate more quickly, while on the other hand, they become more dependent on the host cell for survival. This vulnerability can be exploited by identifying and therapeutically inhibiting the host pathways that are essential for pathogen survival. The significance of our research is in predicting the precise pathways lost during a pathogens evolutionary adaptation to parasitism and validating these predictions through targeted in vitro growth assays and an unbiased metabolomic survey of the host-pathogen interface.

genomics↗

bioRxiv2023

PoMeLo: a systematic computational approach to predicting metabolic loss in pathogen genomes

BackgroundGenome streamlining, the process by which genomes become smaller and encode fewer genes over time, is a common phenomenon among pathogenic bacteria. This reduction is driven by selection for faster replication and minimized energy expenditure in a nutrientrich environment. As pathogens evolve to become more reliant on the host, metabolic genes and resulting capabilities are lost in favor of siphoning metabolites from the host. Characterizing genome streamlining, gene loss, and pathway degradation can be useful in assessing pathogen metabolic dependency on host metabolism and identifying potential targets for host-directed therapeutics. ResultsPoMeLo (Predictor of Metabolic Loss) is a novel evolutionary genomics-guided computational approach for identifying metabolic gaps in the genomes of pathogenic bacteria. PoMeLo leverages a centralized public database of high-quality genomes and annotations and allows the user to compare an unlimited number of genomes across individual genes and pathways. PoMeLo runs locally using user-friendly prompts in a matter of minutes and generates tabular and visual outputs for users to compare predicted metabolic capacity between groups of bacteria and individual species. Each pathway is assigned a Predicted Metabolic Loss (PML) score to assess the magnitude of genome streamlining. Optionally, PoMeLo places results in an evolutionary context by including phylogenetic relationships in visual outputs. It can also initially compute phylogenetically-weighted mean genome sizes to identify genome streamlining events. Here we describe PoMeLo and demonstrate its use in identifying metabolic gaps in genomes of pathogenic Treponema species. ConclusionsPoMeLo represents an advance over existing methods for identifying metabolic gaps in genomic data, allowing comparison across large numbers of genomes and placing the resulting data in a phylogenetic context. PoMeLo is freely available for academic and nonacademic use at https://github.com/czbiohub-sf/pomelo.

bioinformatics↗

bioRxiv2022

AIRRscape: an interactive tool for exploring B-cell receptor repertoires and antibody responses

The sequencing of antibody repertoires of B-cells at increasing coverage and depth has led to the identification of vast numbers of immunoglobulin heavy and light chains. However, the size and complexity of these Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) datasets makes it difficult to perform exploratory analyses. To aid in data exploration, we have developed AIRRscape, an R Shiny-based interactive web browser application that enables B-cell receptor (BCR) and antibody feature discovery through comparisons among multiple repertoires. Using AIRR-seq data as input, AIRRscape starts by aggregating and sorting repertoires into interactive and explorable bins of germline V-gene, germline J-gene, and CDR3 length, providing a high-level view of the entire repertoire. Interesting subsets of repertoires can be quickly identified and selected, and then network topologies of CDR3 motifs can be generated for further exploration. Here we demonstrate AIRRscape using patient BCR repertoires and sequences of published monoclonal antibodies to investigate patterns of humoral immunity to three viral pathogens: SARS-CoV-2, HIV-1, and DENV (dengue virus). AIRRscape reveals convergent antibody sequences among datasets for all three pathogens, although HIV-1 antibody datasets display limited convergence and idiosyncratic responses. We have made AIRRscape available on GitHub to encourage its open development and use by immuno-informaticians, virologists, immunologists, vaccine developers, and other scientists that are interested in exploring and comparing multiple immune receptor repertoires. Author SummaryTechnological advances in next generation sequencing have allowed for broad experimental sampling of immune repertoires, providing insight into how our immune system responds to infection, vaccination, autoimmunity, and cancer. The scale of these "big data", however, make it difficult to bioinformatically extract the key sequence features that are shared across multiple repertoires. With AIRRscape, we enable large-scale immune repertoire visualization and analysis that requires no knowledge of the command line or advanced programming. By providing the community with an open-source, interactive, and user-friendly interface, we reduce the barriers to exploring immune repertoires at scale. We demonstrate the use of AIRRscape to characterize features of immune responses to viral infection that are shared across multiple repertoire datasets.

immunology↗

bioRxiv2022

Converting non-neutralizing SARS-CoV-2 antibodies targeting conserved epitopes into broad-spectrum inhibitors through receptor blockade

All but one of the authorized monoclonal antibody-based treatments for SARS-CoV-2 are largely ineffective against Omicron, highlighting the critical need for biologics capable of overcoming SARS-CoV-2 evolution. These mostly ineffective therapeutic antibodies target epitopes that are not highly conserved. Here we describe broad-spectrum SARS-CoV-2 inhibitors developed by tethering the SARS-CoV-2 receptor, angiotensin-converting enzyme 2 (ACE2), to antibodies that are known to be non-neutralizing, but which target highly conserved epitopes in the viral spike protein. These inhibitors, called Receptor-blocking conserved non-neutralizing Antibodies (ReconnAbs), potently neutralize all SARS-CoV-2 variants of concern (VOC), including Omicron. Neutralization potency is dependent on both the binding and inhibitory ReconnAb components as activity is lost when the linker joining the two is severed. In addition, a bifunctional ReconnAb, made by linking ACE2 to a bispecific antibody targeting two non-overlapping conserved epitopes, defined here, shows sub-nanomolar neutralizing activity against all VOCs, including Omicron. Given their conserved targets and modular nature, ReconnAbs have the potential to act as broad- spectrum therapeutics against SARS-CoV-2 and other emerging pandemic diseases.

biochemistry↗

bioRxiv2019

Adaption of a Conventional ELISA to a 96-well ELISA-Array for Measuring the Antibody Responses to Influenza virus proteins, viruses and vaccines

We describe an adaptation of conventional ELISA methods to an ELISA-Array format using non-contact Piezo printing of up to 30 spots of purified recombinant viral fusion proteins, vaccine and virus on 96 well high-protein binding plates. Antigens were printed in 1 nanoliter volumes of protein stabilizing buffer using as little as 0.25 nanograms of protein, 2000-fold less than conventional ELISA. The performance of the ELISA-Array was demonstrated by serially diluting n=8 human post-flu vaccination plasma samples starting at a 1/1000 dilution and measuring binding to the array of Influenza antigens. Plasma polyclonal antibody levels were detected using a cocktail of biotinylated anti-human kappa and lambda light chain antibodies, followed by a Streptavidin-horseradish peroxidase conjugate and the dose-dependent signal was developed with a precipitable TMB substrate. Intra- and inter-assay precision of absorbance units among the eight donor samples showed mean CVs of 4.8% and 10.8%, respectively. The plasma could be differentiated by donor and antigen with titer sensitivities ranging from 1 x 103 to 4 x 106, IC50 values from 1 x 104 to 9 x 106, and monoclonal antibody sensitivities in the ng/mL range. Equivalent sensitivities of ELISA versus ELISA-Array, compared using plasma and an H1N1 HA trimer, were achieved on the ELISA-Array printed at 0.25ng per 200um spot and 1000ng per ELISA 96-well. Vacuum-sealed array plates were shown to be stable when stored for at least 2 days at ambient temperature and up to 1 month at 4-8{degrees}C. By the use of any set of printed antigens and analyte matrices the methods of this multiplexed ELISA-Array format can be broadly applied in translational research.

immunology↗

bioRxiv2019

Functional characterization and lineage analysis of broadly neutralizing human antibodies against dengue virus identified by single B cell transcriptomics

Eliciting broadly neutralizing antibodies (bNAbs) against the four dengue virus serotypes (DENV1-4) that are spreading into new territories is an important goal of vaccine design. To delineate bNAb targets, we characterized 28 monoclonal antibodies belonging to expanded and hypermutated clonal families identified by transcriptomic analysis of single plasmablasts from DENV-infected individuals. Among these, we identified two somatically related bNAbs that potently neutralized DENV1-4. Mutagenesis studies revealed that the major recognition determinants of these bNAbs are in E protein domain I, distinct from the only known class of human bNAbs against flaviviruses with a well-defined epitope. B cell repertoire analysis from acute-phase peripheral blood suggested a memory origin and divergent somatic hypermutation pathways for these bNAbs, and a limited number of mutations was sufficient for neutralizing activity. Our study suggests multiple B cell evolutionary pathways leading to DENV bNAbs targeting a novel epitope that can be exploited for vaccine design.

microbiology↗

bioRxiv2019

Functional Enrichment and Analysis of Antigen-Specific Memory B Cell Antibody Repertoires in PBMCs

Phenotypic screening of antigen-specific antibodies in human blood is a common diagnostic test for infectious agents and a correlate of protection after vaccination. In addition to long-lived antibody secreting plasma cells residing in the bone marrow, memory B cells are a latent source of antigen-experienced, long-term immunity that can be found at low frequencies in circulating PBMCs. Assessing the genotype, clonal frequency, quality, and function of antibodies resulting from an individuals persistent memory B cell repertoire can help inform the success or failure of immune protection. We have applied ELISPOT cell culture methods to functionally expand the memory repertoire from PBMCs and clonally map monoclonal antibodies from this population. We show that combining deep sequencing of stimulated memory B cell repertoires with retrieving single antigen-specific cells is a promising approach in evaluating the latent, functional B cell memory in PBMCs.

immunology↗