Biology subjects

Zeller, M.

Publications and source records attributed to Zeller, M..

11 recordsLinked to original sources

bioRxiv2026

Comparative Distribution of α2,3- and α2,6-Linked Sialic Acid Receptors and Influenza A(H5N1) Virus Binding in Sheep, Goats, and Alpacas

Highly pathogenic avian influenza virus (HPAIV) H5N1 continues to pose a significant threat to animal and human health. Since 2022, an expanded host range has been observed, as illustrated by the H5N1 outbreak in dairy cows. Other minor livestock species, such as sheep, goats, and alpacas, have also tested positive for H5N1 for the first time, raising concerns about its impact on previously overlooked livestock species. In this study, we first characterized the distribution of sialic acid (SA) receptors across respiratory and non-respiratory tissues of sheep, goats, and alpacas using Maackia amurensis (SA 2,3) and Sambucus nigra (SA 2,6) lectins. We found that both SA receptors are present in all tissues across species, with notable differences in their distribution and abundance. Next, we developed recombinant LPAIV H5N1 viruses over a laboratory-adapted backbone to evaluate tissue-specific virus binding profiles. The results show that a representative H5N1 virus from clade 2.3.4.4b binds effectively to respiratory and non-respiratory tissues across all species. The strongest virus binding was observed in sheep, followed by goats and, lastly, alpacas. Similar binding patterns were observed with an LPAIV version of clade 2.3.4.4b and a Gs/Gd lineage precursor prototype virus. Finally, we show that H1N1 and H3N2 viruses also bind to respiratory tissues of sheep and goats. These findings provide important insights into the potential susceptibility of minor livestock species to HPAIV H5N1 and other influenza subtypes. Our results contribute to a better understanding of influenza tissue tropism across livestock species and its potential implications for zoonotic transmission.

microbiology↗

bioRxiv2026

Pan-Coronavirus Protease Engagement and Differentiated Pharmacology of Antiviral Candidate CMX990

COVID-19 highlighted the need for antivirals that can be rapidly deployed against both current and future coronavirus threats. CMX990 is a clinical stage coronavirus main protease (Mpro) inhibitor bearing a unique trifluoromethoxymethyl ketone warhead. Here, we broadly evaluate its pan-coronavirus target engagement, antiviral breadth, and pharmacologic differentiation. Across a reporter panel of 24 Mpro enzymes spanning alpha-, beta-, delta-, and gamma-coronaviruses, CMX990 retained robust potent activity, including against nirmatrelvir-resistant SARS-CoV-2 variants. In direct comparison, nirmatrelvir and ensitrelvir showed diminished potency against non-SARS-CoV-2 coronaviruses. Live-virus assays corroborated this breadth, with potent, selective activity against SARS-CoV-2, SARS-CoV-1, MERS-CoV, and additional human coronaviruses. Structural studies revealed a conserved covalent binding mode centered on the catalytic Cys of coronavirus Mpro. In serial-passage studies, resistance emerged only after approximately twice as many serial passages under CMX990 selection as under nirmatrelvir selection, without selecting for the canonical nirmatrelvir-resistance substitution E166V. Extracellular washout experiments revealed superior persistence of antiviral activity relative to nirmatrelvir, consistent with durable target engagement. In a murine SARS-CoV-2 infection model, once-daily CMX990 protected against weight loss and reduced lung viral titers to near baseline levels. Collectively, these findings identify CMX990 as a structurally and functionally validated pan-coronavirus protease inhibitor supporting its potential as a pandemic-ready antiviral candidate.

pharmacology and toxicology↗

bioRxiv2026

High Resolution Multi-Pass Astral Analyzer Quantification Enables Highly Multiplexed 35-Plex Tandem Mass Tag Proteomics

Tandem mass tags (TMT) allow highly multiplexed and thus high-throughput, precisely quantitative proteomic analysis. Incorporation of additional deuterated reporter channels has near-doubled the multiplexation achieved with Thermo Scientific TMTpro reagents from 18 to 35-plex but requires extremely high [~]100k analyzer resolving power at m/z 128 to differentiate and quantify reporter ion channels, far beyond any single reflection time-of-flight analyzer, and exceeding the multi-reflection Thermo Scientific Astral analyzer in its standard operation. A multi-pass mode of Astral operation has been developed for the Thermo Scientific Orbitrap Astral Zoom mass spectrometer that triples the ion path to 90 m, more than doubling resolving power for a narrow m/z range. This "TMT HR mode" has been integrated into a new method of TMT proteomic analysis that splits regular MS2 analysis of labeled peptides into paired measurements comprising wide mass range scans for peptide identification, and TMT HR mode scans for reporter ion quantification. The method has been shown to accurately quantify 32-plex labeled HeLa protein lysate and provide far greater depth of analysis as state-of-the-art Orbitrap-only methods, while analysis of 11-plex labeled yeast showed no analytical depth sacrificed vs regular Orbitrap Astral TMT analysis. Further comparative measurements of a 2-cell line 35-plex sample demonstrated greater analytical depth, and similar quantitative precision, to "gold standard" Orbitrap MS3 methods.

biochemistry↗

bioRxiv2025

Multi-site Assessment of Methods for Cell Preservation Upstream of Single Cell RNA Sequencing

Single cell RNA sequencing (scRNA-seq) is a revolutionary technique to identify cell types and their molecular phenotype in heterogeneous biological specimens. ScRNA-seq typically requires fresh, high quality single cell suspensions that are processed immediately to preserve their molecular profiles. This presents a challenge for samples with long preparation times and prevents collection at remote sites lacking the required instrumentation for sample processing. Recently, several commercial assays have been released that enable sample preservation at the time of collection either via fixation or cryopreservation, allowing for sample processing to occur months after the initial collection. The Association of Biomolecular Research Facilities (ABRF) DNA Sequencing (DSRG) and Genomics Bioinformatics (GBiRG) Research Groups have undertaken a cross-platform, multi-site study to assess the performance and reproducibility of three platforms: a) 10x Genomics FLEX, b) Parse Bioscience Evercode WT v2 and c) Honeycomb Bio HIVE. Total leukocytes were isolated from a single healthy individual using the EasySep RBC depletion reagent. Cells were then characterized by collecting a 21-color flow cytometry dataset for reference and the remaining material was used for scRNA-seq procedures where different sites then processed either the fixed or cryopreserved cells for each method. We evaluated performance of each method across traditional scRNA-seq quality control metrics and analysis applications, including gene/transcript detection sensitivity, cell type discovery and annotation, and differential expression. We demonstrate that data from the methods tested can be effectively integrated and produce concordant results with regard to cell type annotation and relative abundance, though we observe platform-specific differences in the expression of a subset of genes. Preservation-based methods also show better retention of fragile granulocyte populations compared with fresh samples processed using the 10x 3 workflow. The improvements to preservation methods are changing the way research is conducted and our thorough investigation into the performance of each method provides a valuable resource to help scientists determine the most appropriate single cell preservation workflow given their sample collection logistics and laboratory infrastructure constraints.

genomics↗

bioRxiv2025

Commercially Purchased and In-House Bred C57BL/6 Mice with Different Gut Microbiota Exhibit Distinct Indomethacin-Induced Toxicities

Non-steroidal anti-inflammatory drug (NSAID)-induced toxicities are a significant clinical problem, yet the factors influencing these outcomes remain incompletely understood. Here, we investigated the impact of mouse vendor on indomethacin-induced injury using C57BL/6 mice from different breeding facilities (in-house "Tar Heel" and commercial Charles River). We found that Tar Heel mice exhibited significantly enhanced susceptibility to indomethacin toxicity, characterized by greater body weight loss, increased ileal ulceration, elevated fecal lipocalin-2 levels, and higher goblet cell numbers in ileum compared to Charles River mice. Importantly, whole genome metagenomic analysis revealed distinct baseline gut microbiomes between the two types of mice. Notably, Tar Heel mice showed higher abundances of {beta}-glucuronidase (GUS)-producing bacteria, particularly those expressing Loop-1 GUS enzymes, and elevated levels of mucolytic enzyme-encoding bacteria. These differences suggest that enhanced indomethacin toxicity observed in Tar Heel mice may be related to functional changes in their gut microbiome, which may predispose to an exaggerated response to NSAID exposure. Together, our findings demonstrate that vendor-specific differences significantly influence NSAID-induced intestinal toxicity and highlight the importance of considering mouse sources and gut microbial compositions in experimental design. Moreover, we highlight potential functional roles that gut microbes play in host-indomethacin interactions.

microbiology↗

bioRxiv2024

PRRSV-2 variant classification: a dynamic nomenclature for enhanced monitoring and surveillance

Existing genetic classification systems for porcine reproductive and respiratory syndrome virus 2 (PRRSV-2), such as restriction fragment length polymorphisms (RFLPs) and sub-lineages, are unreliable indicators of genetic relatedness or lack sufficient resolution for epidemiological monitoring routinely conducted by veterinarians. Here, we outline a fine-scale classification system for PRRSV-2 genetic variants in the U.S. Based on >25,000 U.S. open-reading-frame 5 (ORF5) sequences, sub-lineages were divided into genetic variants using a clustering algorithm. Through classifying new sequences every three months and systematically identifying new variants across eight years, we demonstrated that prospective implementation of the variant classification system produced robust, reproducible results across time and can dynamically accommodate new genetic diversity arising from virus evolution. From 2015 and 2023, 118 variants were identified, with [~]48 active variants per year, of which 26 were common (detected >50 times). Mean within-variant genetic distance was 2.4% (max: 4.8%). The mean distance to the closest related variant was 4.9%. A routinely updated webtool (https://stemma.shinyapps.io/PRRSLoom-variants/) was developed and is publicly available for end-users to assign newly generated sequences to a variant ID. This classification system relies on U.S. sequences from 2015 onwards; further efforts are required to extend this system to older or international sequences. Finally, we demonstrate how variant classification can better discriminate between previous and new strains on a farm, determine possible sources of new introductions into a farm/system, and track emerging variants regionally. Adoption of this classification system will enhance PRRSV-2 epidemiological monitoring, research, and communication, and improve industry responses to emerging genetic variants. ImportanceThe development and implementation of a fine-scale classification system for PRRSV-2 genetic variants represents a significant advancement for monitoring PRRSV-2 occurrence in the swine industry. Based on systematically-applied criteria for variant identification using national-scale sequence data, this system addresses the shortcomings of existing classification methods by offering higher resolution and adaptability to capture emerging variants. This system provides a stable and reproducible method for classifying PRRSV-2 variants, facilitated by a freely available and regularly updated webtool for use by veterinarians and diagnostic labs. Although currently based on U.S. PRRSV-2 ORF5 sequences, this system can be expanded to include sequences from other countries, paving the way for a standardized global classification system. By enabling accurate and improved discrimination of PRRSV-2 genetic variants, this classification system significantly enhances the ability to monitor, research, and respond to PRRSV-2 outbreaks, ultimately supporting better management and control strategies in the swine industry.

microbiology↗

bioRxiv2024

Narrow window data-independent acquisition on the Orbitrap Astral Mass Spectrometer enables fast and deep coverage of the plasma glycoproteome

Recently, a conceptually new mass analyzer was introduced by pairing a quadrupole Orbitrap mass spectrometer with an asymmetric track lossless (Astral) analyzer. This system provides >200-Hz MS/MS scanning speed, high resolving power and sensitivity, and low-ppm mass accuracy. This instrument allows a narrow-window data-independent (nDIA) strategy, improving sensitivity and reproducibility even when using very short LC gradients. Although this represents a new technical milestone in peptide-centric proteomics, this new system has not yet been evaluated for the analyses of very complex and clinically important proteomes, such as represented by the plasma glycoproteome. Here, we evaluated the Orbitrap Astral mass spectrometer for the analysis of the plasma glycoproteome, and pioneer a dedicated nDIA workflow, themed nGlycoDIA. With substantially adjusted parameters and varying collision energies, nGlycoDIA has clear benefits for plasma glycoproteomics. We tested our method both in glycopeptide enriched and crude plasma, leading to the identification of more than 3000 unique glycoPSMs from 181 glycoproteins, covering a dynamic range of 7 orders of magnitude in the enriched plasma sample in just 40 minutes. In addition, we detect for the first time several glycosylated cytokines that have a reported plasma concentration in the ng/L range. Furthermore, shortening the gradient to 10 min still allows the detection of almost 2500 unique glycoPSMs from enriched plasma, indicating that high-throughput indepth clinical plasma glycoproteomics may be within reach.

biochemistry↗

bioRxiv2024

Phylogenetic-based methods for fine-scale classification of PRRSV-2 ORF5 sequences: a comparison of their robustness and reproducibility

Disease management and epidemiological investigations of porcine reproductive and respiratory syndrome virus-type 2 (PRRSV-2) often rely on grouping together highly related sequences. In the USA, the last five years have seen a major paradigm shift within the swine industry when classifying PRRSV-2, beginning to move away from RFLP (restriction fragment length polymorphisms)-typing and adopting the use of phylogenetic lineage-based classification. However, lineages and sub-lineages are large and genetically diverse, and the rapid mutation rate of PRRSV coupled with the global prevalence of the disease has made it challenging to identify new and emerging variants. Thus, within the lineage system, a dynamic fine-scale classification scheme is needed to provide better resolution on the relatedness of PRRSV-2 viruses to inform disease management and monitoring efforts and facilitate research and communication surrounding circulating PRRSV viruses. Here, we compare potential fine-scale systems for classifying PRRSV-2 variants (i.e., genetic clusters of closely related ORF5 sequences at finer scales than sub-lineage) using a database of 28,730 sequences from 2010 to 2021, representing >55% of the U.S. pig population. In total, we compared 140 approaches that differed in their tree-building method, criteria, and thresholds for defining variants within phylogenetic trees using TreeCluster. Three approaches produced epidemiologically meaningful variants (i.e., [≥]5 sequences per cluster), and resulted in reproducible and robust outputs even when the input data or input phylogenies were changed. In the three best performing approaches, the average genetic distance amongst sequences belonging to the same variant was 2.1 - 2.5%, and the genetic divergence between variants was 2.5-2.7%. Machine learning classification algorithms were also trained to assign new sequences to an existing variant with >95% accuracy, which shows that newly generated sequences could be assigned without repeating the phylogenetic and clustering analyses. Finally, we identified 73 sequence-clusters (dated <1 year apart with close phylogenetic relatedness) associated with circulation events on single farms. The percent of farm sequence-clusters with an ID change was 6.5-8.7% for our best approaches. In contrast, [~]43% of farm sequence-clusters had variation in their RFLP-type, further demonstrating how our proposed fine-scale classification system addresses shortcomings of RFLP-typing. Through identifying robust and reproducible classification approaches for PRRSV-2, this work lays the foundation for a fine-scale system that would more reliably group related field viruses and provide better improved clarity for decision-making surrounding disease management.

bioinformatics↗

bioRxiv2023

Parallelized Acquisition of Orbitrap and Astral Analyzers Enables High-Throughput Quantitative Analysis.

The growing trend towards high-throughput proteomics demands rapid liquid chromatography-mass spectrometry (LC-MS) cycles that limit the available time to gather the large numbers of MS/MS fragmentation spectra required for identification. Orbitrap analyzers scale performance with acquisition time, and necessarily sacrifice sensitivity and resolving power to deliver higher acquisition rates. We developed a new mass spectrometer that combines a mass resolving quadrupole, the Orbitrap and the novel Asymmetric Track Lossless (Astral) analyzer. The new hybrid instrument enables faster acquisition of high-resolution accurate mass (HRAM) MS/MS spectra compared to state-of-the-art mass spectrometers. Accordingly, new proteomics methods were developed that leverage the strengths of each HRAM analyzer, whereby the Orbitrap analyzer performs full scans with high dynamic range and resolution, synchronized with Astral analyzers acquisition of fast and sensitive HRAM MS/MS scans. Substantial improvements are demonstrated over previous methods using current state-of-the-art mass spectrometers. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/543408v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1eedfdeorg.highwire.dtl.DTLVardef@1ab7939org.highwire.dtl.DTLVardef@a3b2f8org.highwire.dtl.DTLVardef@13ac46b_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2021

Predicting the evolution of Lassa Virus endemic area and population at risk over the next decades

Lassa fever is listed among the diseases that pose the greatest risks to public health by the World Health Organization. This severe viral hemorrhagic fever is caused by Lassa virus, a zoonotic pathogen that repeatedly spills over to humans from its rodent reservoirs. It is currently not known how climate change, transformations in land use, and human population growth could affect the endemic area of this virus, currently limited to parts of West Africa. By exploring the environmental data associated with virus occurrence, we show how temperature, precipitation and the presence of pastures determine ecological suitability for virus circulation. We project that regions in Central and East Africa will likely become suitable for Lassa virus over the next decades and estimate that the total population living in areas suitable for Lassa virus may grow from about 100 million to 700 million by 2070. By analysing geotagged viral genomes, we find that in the event of Lassa virus being introduced into a new suitable region, its spread might remain spatially limited over the first decades. Our results highlight how the endemic area of Lassa virus may expand well beyond West Africa in the next decades due to human impact on the environment, putting hundreds of million more people at risk of infection.

microbiology↗

bioRxiv2021

Successional stages in infant gut microbiota maturation

BackgroundDisturbances in the primary colonization of the infant gut can result in life-long consequences and have been associated with a range of host conditions. Although early life factors have been shown to affect the infant gut microbiota development, our current understanding of the human gut colonization in early life remains limited. To gain more insights in the unique dynamics of this rapidly evolving ecosystem, we investigated the microbiota over the first year of life in eight densely sampled infants (total number of samples, n=303). To evaluate gut microbiota maturation transition towards an adult configuration, we compared the microbiome composition of the infants to the Flemish Gut Flora Project population (n=1,106). ResultsWe observed the infant gut microbiota to mature through three distinct, conserved stages of ecosystem development. Across these successional gut microbiota maturation stages, genus predominance was observed to shift from Escherichia over Bifidobacterium to Bacteroides. Both disease and antibiotic treatment were observed to be associated occasionally with gut microbiota maturation stage regression, a transient setback in microbiota maturation dynamics. Although the studied microbiota trajectories evolved to more adult-like constellations, microbiome community typing against the background of the Flemish Gut Flora Project (FGFP) cohort clustered all infant samples within the (in adults) potentially dysbiotic Bact2 enterotype. ConclusionWe confirmed similarities between infant gut microbial colonization and adult dysbiosis. A profound knowledge about the primary gut colonization process in infants might provide crucial insights into how the secondary colonization of a dysbiotic adult gut can be redirected.

microbiology↗