Biology subjects

Chiang, Y.

Publications and source records attributed to Chiang, Y..

4 recordsLinked to original sources

bioRxiv2024

Orthrus: an AI-powered, cloud-ready, and open-source hybrid approach for metaproteomics

While metaproteomics provides invaluable insight into microbial communities and functions, significant bioinformatics challenges persist due to data complexity and the limitations of database searching. We introduce Orthrus, a hybrid approach combining transformer-based de novo sequencing (Casanovo) and database searching with rescoring (Sage+Mokapot). Benchmarking against PEAKS(R)11, MaxQuant, and MetaNovo, Orthrus demonstrates high peptide outputs, taxonomic diversity, and proteome coverage. Orthrus is Python-based and accessible to all via Google Colaboratory.

bioinformatics↗

bioRxiv2024

Anubis: a multi-level authentication scale for ancient proteins using random forest classification

Deamidation is a time-dependent, post-translational modification with wide applications in clinical proteomics and palaeoproteomics as ageing indicators and authentication markers. Despite its significance, the use of deamidation for authenticating ancient proteins remains controversial, primarily due to variability in deamidation kinetics and context-specific protein preservation. We propose Anubis, an open-source, Python-based pipeline to evaluate relative deamidation patterns and authenticate ancient proteins. Anubis leverages random forest classification based on a range of tandem mass spectrometry-based features and physico-chemical characteristics. We use a combination of ancient and experimentally degraded beta-lactoglobulin to demonstrate that Anubis can authenticate a putative ancient dairy protein using position-specific deamidation patterns, relative deamidation (asparagine vs. glutamine), and overall modification patterns using trypsin processed in the same batch as a baseline. This multi-level approach addresses the complexities of ancient protein deamidation and paves the way for automated, reliable authentication across different archaeological substrates.

bioinformatics↗

bioRxiv2023

Benchmarking the identification of a single degraded protein to explore optimal search strategies for ancient proteins

Palaeoproteomics is a rapidly evolving discipline, and practitioners are constantly developing novel strategies for the analyses and interpretations of complex, degraded protein mixtures. The community has also established standards of good practice to interrogate our data. However, there is a lack of a systematic exploration of how these affect the identification of peptides, post-translational modifications (PTMs), proteins and their significance (through the False Discovery Rate) and correctness. We systematically investigated the performance of a wide range of sequencing tools and search engines in a controlled system: the experimental degradation of the single purified bovine {beta}-lactoglobulin (BLG), heated at 95 {degrees}C and pH 7 for 0, 4 and 128 days. We target BLG since it is one of the most robust and ubiquitous proteins in the archaeological record. We tested different reference database choices, a targeted dairy protein one, and the whole bovine proteome and the three digestion options (tryptic-, semi-tryptic- and non-specific searches), in order to evaluate the effects of search space and the identification of peptides. We also explored alternative strategies, including open search that allows for the global identification of PTMs based upon wide precursor mass tolerance and de novo sequencing to boost sequence coverage. We analysed the samples using Mascot, MaxQuant, Metamorpheus, pFind, Fragpipe and DeNovoGUI (pepNovo+, DirecTag, Novor), benchmarked these tools and discuss the optimal strategy for the characterisation of ancient proteins. We also studied physicochemical properties of the BLG that correlate with bias in the identification coverage.

bioinformatics↗

bioRxiv2020

Capturing and Recreating Diverse Antibody Repertoires as Multivalent Recombinant Polyclonal Antibody Drugs

Plasma-derived polyclonal antibodies are polyvalent drugs used for many important clinical indications that require modulation of multiple drug targets simultaneously, including emerging infectious disease and transplantation. However, plasma-derived drugs suffer many problems, including low potency, impurities, constraints on supply, and batch-to-batch variation. In this study, we demonstrated proofs-of-concept for a technology that uses microfluidics and molecular genomics to capture diverse mammalian antibody repertoires as multivalent recombinant drugs. These "recombinant hyperimmune" drugs comprised thousands to tens of thousands of antibodies and were derived from convalescent human donors, or vaccinated human donors or immunized mice. Here we used our technology to build a highly potent recombinant hyperimmune for Severe Acute Respiratory Syndrome Coronavirus-2 (SARS CoV-2) in less than three months. We also validated a recombinant hyperimmune for Zika virus disease that abrogates antibody-dependent enhancement (ADE) through Fc engineering. For patients with primary immune deficiency (PID), we built high potency polyvalent recombinant hyperimmunes against pathogens that commonly cause serious lung infections. Finally, to address the limitations of rabbit-derived anti-thymocyte globulin (ATG), we generated a recombinant human version and demonstrated in vivo function against graft-versus-host disease (GVHD). Recombinant hyperimmunes are a novel class of drugs that could be used to target a wide variety of other clinical applications, including cancer and autoimmunity.

immunology↗