Biology subjects

Gu, Q.

Publications and source records attributed to Gu, Q..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Direct Nuclear Delivery of Proteins on Living Plant via Partial Enzymatic Cell Wall Digestion

While many variations of protein delivery methods have been described, it can still be difficult or inefficient to introduce exogenous proteins into plants. A major barrier to progress is the cell wall which is primarily composed of polysaccharides and thus only permeable to small molecules. Here, we report a partial enzymatic cell wall digestion-mediated uptake method that efficiently delivers protein into the nucleus of plant cells. Such a method allowed efficient nuclear delivery of GFP proteins into Arabidopsis root cells throughout all cell layers. This study establishes that a partial enzymatic cell wall degradation could enable a myriad of plant biotechnology applications that rely on functional protein delivery into walled plant cells.

bioengineering↗

bioRxiv2024

Multi-omics analysis of virus-permissive versus hostile cellular states reveals protein networks controlling virus infection

The capacity of host cells to sustain or restrict virus infection is influenced by their proteome. Understanding the compendium of proteins defining cellular permissiveness is key to many questions in fundamental virology. Here, we apply a multiomic approach to determine the proteins that are associated with highly permissive, intermediate, and hostile cellular states. We observed two groups of differentially regulated genes: i) with robust changes in mRNA and protein levels, and ii) with protein/RNA discordances. Many of the latter are classified as interferon stimulated genes (ISGs) but have no reported antiviral activity. This suggests that IFN-dependent changes in mRNA levels do not imply antiviral function. Phosphoproteomics revealed an additional regulatory layer involving non-signalling proteins with altered phosphorylation. Indeed, we confirmed that several permissiveness-associated proteins with changes in abundance or phosphorylation regulate infection fitness. Altogether, our study provides a comprehensive and systematic map of the cellular alterations driving virus susceptibility.

pathology↗

bioRxiv2024

Omicron-specific ultra-potent SARS-CoV-2 neutralizing antibodies targeting the N1/N2 loop of Spike N-terminal domain

A multitude of functional mutations continue to emerge on the N-terminal domain (NTD) of the spike protein in SARS-CoV-2 Omicron subvariants. Understanding the immunogenicity of Omicron NTD and the properties of antibodies elicited by it is crucial for comprehending the impact of NTD mutations on viral fitness and guiding vaccine design. In this study, we find that most of NTD-targeting antibodies isolated from individuals with BA.5/BF.7 breakthrough infection (BTI) are ancestral (wildtype or WT)-reactive and non-neutralizing. Surprisingly, we identified five ultra-potent neutralizing antibodies (NAbs) that can only bind to Omicron but not WT NTD. Structural analysis revealed that they bind to a unique epitope on the N1/N2 loop of NTD and interact with the receptor-binding domain (RBD) via the light chain. These Omicron-specific NAbs achieve neutralization through ACE2 competition and blockage of ACE2-mediated S1 shedding. However, BA.2.86 and BA.2.87.1, which carry insertions or deletions on the N1/N2 loop, can evade these antibodies. Together, we provided a detailed map of the NTD-targeting antibody repertoire in the post-Omicron era, demonstrating their vulnerability to NTD mutations enabled by its evolutionary flexibility, despite their potent neutralization. These results highlighted the importance of considering the immunogenicity of NTD in vaccine design. Author SummaryCOVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to be a major global public health concern four years after its emergence. The N-terminal domain (NTD) is a critical component of the spike glycoprotein, which is pivotal for SARS-CoV-2 cellular entry and serves as a primary target for antibody therapeutics and vaccine development. Characterizing the properties of antibodies elicited by NTD of Omicron sublineages is crucial for understanding viral evolution and guiding vaccine design. Here, we show that Omicron infection after vaccination induces majorly non-neutralizing NTD antibodies. Still, we identified a class of ultra-potent neutralizing antibodies (NAbs) which specifically bind to the NTD of Omicron sublineages. These NAbs neutralize the virus by competing with ACE2 and blocking ACE2-mediated S1 shedding. Structural analyses reveal that these antibodies target a unique epitope on the N1/N2 loop of NTD, and intriguingly interact with the receptor-binding domain (RBD) of spike glycoprotein. This class of NAbs with the special binding pattern, are escaped by BA.2.86 and BA.2.87.1 sublineages, shedding light on the role of recently emerged mutations in the N1/N2 loop of NTD. Our findings provide fresh insights into the immunogenicity of Omicron NTD, highlighting its capacity for antibody evasion due to its evolutionary flexibility. This underscores the importance of carefully considering the NTD component in vaccine design.

immunology↗

bioRxiv2024

Humoral immunogenicity comparison of XBB and JN.1 in human infections

The continuous evolution of SARS-CoV-2, particularly the emergence of the BA.2.86/JN.1 lineage replacing XBB lineages, necessitates re-evaluation of current vaccine compositions. Here, we provide a comprehensive analysis of the humoral immune response to XBB and JN.1 human exposures, emphasizing the need for JN.1-lineage-based boosters. We demonstrate the antigenic distinctiveness of XBB and JN.1 lineages in SARS-CoV-2-naive individuals but not in those with prior vaccinations or infections, and JN.1 infection elicits superior plasma neutralization titers against its subvariants. We highlight the strong immune evasion and receptor binding capability of KP.3, supporting its foreseeable prevalence. Extensive analysis of the BCR repertoire, isolating [~]2000 RBD-specific monoclonal antibodies (mAbs) with their targeting epitopes characterized by deep mutational scanning (DMS), underscores the systematic superiority of JN.1-elicited memory B cells (MBCs). Notably, Class 1 IGHV3-53/3-66-derived neutralizing antibodies (NAbs) contribute majorly within wildtype (WT)-reactive NAbs against JN.1. However, KP.2 and KP.3 evade a substantial subset of them, even those induced by JN.1, advocating for booster updates to KP.3 for optimized enrichment. JN.1-induced Omicron-specific antibodies also demonstrate high potency across all Omicron lineages. Escape hotspots of these NAbs have mainly been mutated in Omicron RBD, resulting in higher immune barrier to escape, considering the probable recovery of previously escaped NAbs. Additionally, the prevalence of broadly reactive IGHV3-53/3-66- encoding antibodies and MBCs, and their capability of competing with all Omicron-specific NAbs suggests their inhibitory role on the de novo activation of Omicron-specific naive B cells, potentially explaining the heavy immune imprinting in mRNA-vaccinated individuals. These findings delineate the evolving antibody response to Omicron antigenic shift from XBB to JN.1, and highlight the importance of developing JN.1 lineage, especially KP.3-based vaccine boosters, to enhance humoral immunity against current and future SARS-CoV-2 variants.

immunology↗

bioRxiv2024

Discovering CRISPR-Cas system with self-processing pre-crRNA capability by foundation models

The discovery and functional annotation of CRISPR-Cas systems laid the groundwork for the development of novel CRISPR-based gene editing tools. Traditional similarity- search-based Cas discovery strategies, which rely heavily on local sequence alignment and reference Cas homologs, may overlook a significant number of remote homologs with limited sequence similarity; and it can not be applied directly for functional recognition. With the rapid development of protein large language models (LLMs), protein foundation models are expected to help model Cas systems with limited Cas homologs without extensive task-specific training data; however, the full potential of these models for Cas discovery and functional annotation has yet to be determined. To this end, we present a novel, effective and unified AI framework, CHOOSER (Cas HOmlog Observing and SElf-processing scReening), for alignment-free discovery of novel CRISPR-Cas systems with self-processing precursor CRISPR RNA (pre-crRNA) capability utilizing protein foundation models. CHOOSER successfully retrieved 11 novel homologs of Cas{lambda}, the majority of which are predicted to be able to self-process pre-crRNA, nearly doubling the current catalog. One of the candidates, EphcCas{lambda}, was subsequently experimentally validated for its ability to self-process pre-crRNA, target DNA cleavage, and trans-cleavage and was shown to be a promising candidate for use as a CRISPR-Cas-based pathogen detection system. Overall, our study provides an unprecedented perspective and methodology for discovering novel CRISPR-Cas systems with specific functions using foundation models, underscoring the potential for transforming newly identified Cas homologs into genetic editing tools.

bioinformatics↗

bioRxiv2024

A Machine Learning Framework to Identify the Correlates of Disease Severity in Acute Arbovirus Infection

Most viral diseases display a variable clinical outcome due to differences in virus strain virulence and/or individual host susceptibility to infection. Understanding the biological mechanisms differentiating a viral infection displaying severe clinical manifestations from its milder forms can provide the intellectual framework toward therapies and early prognostic markers. This is especially true in arbovirus infections, where most clinical cases are present as mild febrile illness. Here, we used a naturally occurring vector-borne viral disease of ruminants, bluetongue, as an experimental system to uncover the fundamental mechanisms of virus-host interactions resulting in distinct clinical outcomes. As with most viral diseases, clinical symptoms in bluetongue can vary dramatically. We reproduced experimentally distinct clinical forms of bluetongue infection in sheep using three bluetongue virus (BTV) strains (BTV-1IT2006, BTV-1IT2013 and BTV-8FRA2017). Infected animals displayed clinical signs varying from clinically unapparent, to mild and severe disease. We collected and integrated clinical, haematological, virological, and histopathological data resulting in the analyses of 332 individual parameters from each infected and uninfected control animal. We subsequently used machine learning to identify the key viral and host processes associated with disease pathogenesis. We identified five different fundamental processes affecting the severity of bluetongue: (i) virus load and replication in target organs, (ii) modulation of the host type-I IFN response, (iii) pro-inflammatory responses, (iv) vascular damage, and (v) immunosuppression. Overall, our study using an agnostic machine learning approach, can be used to prioritise the different pathogenetic mechanisms affecting the disease outcome of an arbovirus infection.

microbiology↗

bioRxiv2023

Ferritinophagy is a Druggable Vulnerability of Quiescent Leukemic Stem Cells

Acute myeloid leukemia (AML) remains a challenging hematological malignancy with poor prognosis and limited treatment options. Leukemic stem cells (LSCs) contributes to therapeutic failure, post-therapy relapse and adverse outcome. Here, we investigated the role of quiescence and its associated molecular mechanisms in AML pathogenesis and LSCs functions, and identified potential vulnerabilities for therapeutic intervention. We found that LSC-enriched quiescent cell population exhibited a distinct gene set of prognostic significance in AML patients. Furthermore, this quiescent cells subset displayed heightened autophagic activity with a reliance on ferritinophagy, a selective form of autophagy mediated by Nuclear Receptor Coactivator 4 (NCOA4) regulating iron bioavailability. Inhibition of NCOA4 genetically or chemically showed potent anti-leukemic effects, particularly targeting the LSC compartment. These findings uncover that ferritinophagy inhibition may represent a promising therapeutic strategy for patients with AML. One Sentence SummaryTargeting quiescent leukemic stem cells via NCOA4-dependent ferritinophagy inhibition may improve therapeutic outcomes in acute myeloid leukemia.

cancer biology↗

bioRxiv2023

CryoSTAR: Leveraging Structural Prior and Constraints for Cryo-EM Heterogeneous Reconstruction

Resolving conformational heterogeneity in cryo-electron microscopy (cryo-EM) datasets remains a significant challenge in structural biology. Previous methods have often been restricted to working exclusively on volumetric densities, neglecting the potential of incorporating any pre-existing structural knowledge as prior or constraints. In this paper, we present a novel methodology, cryoSTAR, that harnesses atomic model information as structural regularization to elucidate such heterogeneity. Our method uniquely outputs both coarse-grained models and density maps, showcasing the molecular conformational changes at different levels. Validated against four diverse experimental datasets, spanning large complexes, a membrane protein, and a small single-chain protein, our results consistently demonstrate an efficient and effective solution to conformational heterogeneity with minimal human bias. By integrating atomic model insights with cryo-EM data, cryoSTAR represents a meaningful step forward, paving the way for a deeper understanding of dynamic biological processes.1

biophysics↗

bioRxiv2023

Trans-Lesion Synthesis and Mismatch Repair Pathway Crosstalk Defines Chemoresistance and Hypermutation Mechanisms in Glioblastoma

Almost all Glioblastoma (GBM) are either intrinsically resistant to the chemotherapeutical drug temozolomide (TMZ) or acquire therapy-induced mutations that cause chemoresistance and recurrence. The genome maintenance mechanisms responsible for GBM chemoresistance and hypermutation are unknown. We show that the E3 ubiquitin ligase RAD18 (a proximal regulator of TLS) is activated in a Mismatch repair (MMR)-dependent manner in TMZ-treated GBM cells, promoting post-replicative gap-filling and survival. An unbiased CRISPR screen provides a new aerial map of RAD18-interacting DNA damage response (DDR) pathways deployed by GBM to tolerate TMZ genotoxicity. Analysis of mutation signatures from TMZ-treated GBM reveals a role for RAD18 in error-free bypass of O6mG (the most toxic TMZ-induced lesion), and error-prone bypass of other TMZ-induced lesions. Our analyses of recurrent GBM patient samples establishes a correlation between low RAD18 expression and hypermutation. Taken together we define novel molecular underpinnings for the hallmark tumorigenic phenotypes of TMZ-treated GBM.

cancer biology↗

bioRxiv2023

Single-cell bisulfite-free 5mC and 5hmC sequencing with high sensitivity and scalability

Existing single cell bisulfite-based DNA methylation analysis is limited by low DNA recovery, and the measurement of 5hmC at single-base resolution remains challenging. Here we present a bisulfite-free single-cell whole-genome 5mC and 5hmC profiling technique, named Cabernet, which can characterize 5mC and 5hmC at single-base resolution with high genomic coverage. Cabernet utilizes Tn5 transposome for DNA fragmentation, which enables the discrimination between different alleles for measuring hemi-methylation status. Using Cabernet, we revealed the 5mC, hemi-5mC and 5hmC dynamics during early mouse embryo development, uncovering genomic regions exclusively governed by active or passive demethylation. We show that hemi-methylation status can be used to distinguish between pre- and post-replication cells, enabling more efficient cell grouping when integrated with 5mC profile. The property of Tn5 naturally enables Cabernet to achieve high-throughput single-cell methylome profiling, where we probed mouse cortical neurons and embryonic day 7.5 (E7.5) embryos, and constructed the library for thousands of single cells at high efficiency, demonstrating its potential for analyzing complex tissues at substantially low cost. Together, we present a new way of high-throughput methylome and hydroxymethylome detection at single-cell resolution, enabling efficient analysis of epigenetic status of biological systems with complicated nature such as neurons and cancer cells. Significance StatementMost of current methylation profiling techniques rely on bisulfite treatment, which suffers low DNA recovery. The technique proposed in this study, named Cabernet, can be used to measure 5mC and 5hmC at single-base resolution with high genomic coverage. By using Tn5 transposome, hemi-methylation status can be measured and high-throughput methylome profiling can be achieved. Together, it provides an efficient way to analyze the epigenetic landscape of complicated biological systems.

genomics↗

bioRxiv2023

PhyGCN: Pre-trained Hypergraph Convolutional Neural Networks with Self-supervised Learning

Hypergraphs are powerful tools for modeling complex interactions across various domains, including biomedicine. However, learning meaningful node representations from hypergraphs remains a challenge. Existing supervised methods often lack generalizability, thereby limiting their real-world applications. We propose a new method, Pre-trained Hypergraph Convolutional Neural Networks with Self-supervised Learning (PhyGCN), which leverages hypergraph structure for self-supervision to enhance node representations. PhyGCN introduces a unique training strategy that integrates variable hyperedge sizes with self-supervised learning, enabling improved generalization to unseen data. Applications on multi-way chromatin interactions and polypharmacy side-effects demonstrate the effectiveness of PhyGCN. As a generic framework for high-order interaction datasets with abundant unlabeled data, PhyGCN holds strong potential for enhancing hypergraph node representations across various domains.

bioinformatics↗

bioRxiv2023

Temperature elevation synergises with and enhances the type-I IFN-mediated restriction of MPXV

Fever is an evolutionary conserved host pro-inflammatory immune response that governs the regulation of multiple biological processes to control the outcome of infection. In January 2022, the World Health Organization (WHO) reported a global outbreak in mpox cases with a high incidence of human-to-human transmission. A frequent prodromal symptom of monkeypox virus (MPXV) infection is fever, with a febrile temperature range of 38.3 to 40.5 {degrees}C. However, the outcome of temperature elevation on MPXV infection remains poorly defined. Here, we isolated a circulating strain of MPXV from a patient who presented with fever (38.5 {degrees}C) and rash from the 2022 outbreak. Genomic sequencing identified this isolate to belong to the epidemic Clade IIb.B1. Transcriptomic analysis of infected cells demonstrated this virus to induce a strong IL6 pro-inflammatory immune response, consistent with a role for this pyrogen in the regulation of fever. We identify host-cell temperature at both physiological skin (33 {degrees}C) and clinical febrile temperatures (38.5 and 40 {degrees}C) to be a key determinant in the outcome of infection through the differential regulation of MPXV transcription and associated amplitude of host cytokine response to infection. Incubation of infected cells at 38.5 or 40 {degrees}C led to a restriction or ablation in MPXV replication, respectively. Importantly, this thermal inhibition was reversible upon temperature downshift to 37 {degrees}C without detriment to viral replication fitness. Co-stimulation of the type-I interferon (IFN) response led to a dose- and temperature-dependent inhibition in MPXV replication that restricted the re-establishment of infection upon temperature downshift and withdrawal of IFN as an immune stimulus. Our data identify febrile temperatures associated with mpox disease to be a critical component of the host pro-inflammatory immune response to infection which can synergise with the type-I IFN response to enhance the host-cell mediated restriction of MPXV.

microbiology↗

bioRxiv2023

Antigenicity and infectivity characterization of SARS-CoV-2 BA.2.86

The recently identified SARS-CoV-2 variant, BA.2.86, which carries a substantial number of Spike mutations, has raised a global alarm. An immediate assessment of its antigenic properties and infectivity is necessary. Here, we reveal the distinct antigenicity of BA.2.86 compared with previous variants including XBB.1.5. BA.2.86 significantly evades convalescent plasma from XBB breakthrough infection (BTI) and reinfections. Key mutations that mediate the enhanced resistance include N450D, K356T, L452W, A484K, V483del, and V445H on the RBD, while BA.2.86s NTD mutations and E554K on SD1 also largely contribute. However, we found that BA.2.86 pseudovirus exhibits compromised efficiency of infecting HEK293T-hACE2 cells compared to XBB.1.5 and EG.5, which may be caused by K356T, V483del, and E554K, and could potentially limit BA.2.86s transmissibility. In sum, it appears that BA.2.86 has traded its infectivity for higher immune evasion during long-term host-viral evolution. Close attention should be paid to monitoring additional mutations that could improve BA.2.86s infectivity.

immunology↗

bioRxiv2023

Convergent evolution of SARS-CoV-2 XBB lineages on receptor-binding domain 455-456 enhances antibody evasion and ACE2 binding

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) XBB lineages have achieved dominance worldwide and keep on evolving. Convergent evolution of XBB lineages on the receptor-binding domain (RBD) L455F and F456L is observed, resulting in variants like EG.5, FL.1.5.1, XBB.1.5.70, and HK.3. Here, we show that neutralizing antibody (NAb) evasion drives the convergent evolution of F456L, while the epistatic shift caused by F456L enables the subsequent convergence of L455F through ACE2 binding enhancement and further immune evasion. L455F and F456L evade Class 1 NAbs, reducing the neutralization efficacy of XBB breakthrough infection (BTI) and reinfection convalescent plasma. Importantly, L455F single substitution significantly dampens receptor binding; however, the combination of L455F and F456L forms an adjacent residue flipping, which leads to enhanced NAbs resistance and ACE2 binding affinity. The perturbed receptor-binding mode leads to the exceptional ACE2 binding and NAb evasion, as revealed by structural analyses. Our results indicate the evolution flexibility contributed by epistasis cannot be underestimated, and the evolution potential of SARS-CoV-2 RBD remains high.

immunology↗

bioRxiv2023

Phenotyping the virulence of SARS-CoV-2 variants in hamsters by digital pathology and machine learning

SARS-CoV-2 has continued to evolve throughout the COVID-19 pandemic, giving rise to multiple variants of concern (VOCs) with different biological properties. As the pandemic progresses, it will be essential to test in near real time the potential of any new emerging variant to cause severe disease. BA.1 (Omicron) was shown to be attenuated compared to the previous VOCs like Delta, but it is possible that newly emerging variants may regain a virulent phenotype. Hamsters have been proven to be an exceedingly good model for SARS-CoV-2 pathogenesis. Here, we aimed to develop robust quantitative pipelines to assess the virulence of SARS-CoV-2 variants in hamsters. We used various approaches including RNAseq, RNA in situ hybridization, immunohistochemistry, and digital pathology, including software assisted whole section imaging and downstream automatic analyses enhanced by machine learning, to develop methods to assess and quantify virus-induced pulmonary lesions in an unbiased manner. Initially, we used Delta and Omicron to develop our experimental pipelines. We then assessed the virulence of recent Omicron sub-lineages including BA.5, XBB, BQ.1.18, BA.2 and BA.2.75. We show that in experimentally infected hamsters, accurate quantification of alveolar epithelial hyperplasia and macrophage infiltrates represent robust markers for assessing the extent of virus-induced pulmonary pathology, and hence virus virulence. In addition, using these pipelines, we could reveal how some Omicron sub-lineages (e.g., BA.2.75) have regained virulence compared to the original BA.1. Finally, to maximise the utility of the digital pathology pipelines reported in our study, we developed an online repository containing representative whole organ histopathology sections that can be visualised at variable magnifications (https://covid-atlas.cvr.gla.ac.uk). Overall, this pipeline can provide unbiased and invaluable data for rapidly assessing newly emerging variants and their potential to cause severe disease.

microbiology↗

bioRxiv2023

Repeated Omicron infection alleviates SARS-CoV-2 immune imprinting

The continuous emergence of highly immune evasive SARS-CoV-2 variants, like XBB.1.51,2 and XBB.1.163,4, highlights the need to update COVID-19 vaccine compositions. However, immune imprinting induced by wildtype (WT)-based vaccination would compromise the antibody response to Omicron-based boosters5-9. Vaccination strategies that can counter immune imprinting are critically needed. In this study, we investigated the degree and dynamics of immune imprinting in mouse models and human cohorts, especially focusing on the role of repeated Omicron stimulation. Our results show that in mice, the efficacy of single Omicron-boosting is heavily limited by immune imprinting, especially when using variants antigenically distinct from WT, like XBB, while the concerning situation could be largely mitigated by a second Omicron booster. Similarly, in humans, we found that repeated Omicron infections could also alleviate WT-vaccination-induced immune imprinting and generate high neutralizing titers against XBB.1.5 and XBB.1.16 in both plasma and nasal mucosa. By isolating 781 RBD-targeting mAbs from repeated Omicron infection cohorts, we revealed that double Omicron exposure alleviates immune imprinting by generating a large proportion of highly matured and potent Omicron-specific antibodies. Importantly, epitope characterization using deep mutational scanning (DMS) showed that these Omicron-specific antibodies target distinct RBD epitopes compared to WT-induced antibodies, and the bias towards non-neutralizing epitopes observed in single Omicron exposures due to imprinting was largely restored after repeated Omicron stimulation, together leading to a substantial neutralizing epitope shift. Based on the DMS profiles, we identified evolution hotspots of XBB.1.5 RBD and demonstrated the combinations of these mutations could further boost XBB.1.5s immune-evasion capability while maintaining high ACE2 binding affinity. Our findings suggest the WT component should be abandoned when updating COVID-19 vaccine antigen compositions to XBB lineages, and those who havent been exposed to Omicron yet should receive two updated vaccine boosters.

immunology↗

bioRxiv2023

Structure-informed Language Models Are Protein Designers

This paper demonstrates that language models are strong structure-based protein designers. We present LM-DO_SCPLOWESIGNC_SCPLOW, a generic approach to reprogramming sequence-based protein language models (pLMs), that have learned massive sequential evolutionary knowledge from the universe of natural protein sequences, to acquire an immediate capability to design preferable protein sequences for given folds. We conduct a structural surgery on pLMs, where a lightweight structural adapter is implanted into pLMs and endows it with structural awareness. During inference, iterative refinement is performed to effectively optimize the generated protein sequences. Experiments show that LM-DO_SCPLOWESIGNC_SCPLOW improves the state-of-the-art results by a large margin, leading to 4% to 12% accuracy gains in sequence recovery (e.g., 55.65%/56.63% on CATH 4.2/4.3 single-chain benchmarks, and >60% when designing protein complexes). We provide extensive and in-depth analyses, which verify that LM-DO_SCPLOWESIGNC_SCPLOW can (1) indeed leverage both structural and sequential knowledge to accurately handle structurally non-deterministic regions, (2) benefit from scaling data and model size, and (3) generalize to other proteins (e.g., antibodies and de novo proteins).

bioinformatics↗

bioRxiv2022

Correlated protein modules reflecting functional coordination of interacting proteins are uncovered by single-cell proteomics

Single-cell proteomics has attracted a lot of attention in recent years because it offers more functional relevance than single-cell transcriptomics. However, most work to date focused on cell typing, which has been widely accomplished by single-cell transcriptomics. Here we report the use of single-cell proteomics to measure the correlations between the translational levels of any pair of proteins in a single mammalian cell. In measuring pairwise correlations among [~]1,000 proteins in a population of homogeneous K562 cells in a steady-state condition, we observed multiple correlated protein modules (CPMs), each containing a group of highly positively correlated proteins that are functionally interacting and collectively involved in certain biological functions, such as protein synthesis and oxidative phosphorylation. Some CPMs are shared across different cell types while others are cell-type specific. Widely studied in omics analyses, pairwise correlations are often measured by introducing perturbations to bulk samples. However, some correlations of gene or protein expression in steady-state condition would be masked by perturbation. The single-cell correlations probed in our experiment reflect intrinsic steady-state fluctuations in the absence of perturbation. We note that observed correlations between proteins are experimentally more distinct and functionally more relevant than those between corresponding mRNAs measured in single-cell transcriptomics. By virtue of single-cell proteomics, functional coordination of proteins is manifested through CPMs. Table of Contents Image O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/520903v2_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@10e27corg.highwire.dtl.DTLVardef@857044org.highwire.dtl.DTLVardef@8d9731org.highwire.dtl.DTLVardef@1c149a4_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗