Biology subjects

QIAN, W.-J.

Publications and source records attributed to QIAN, W.-J..

10 recordsLinked to original sources

bioRxiv2026

Cell State Transitions Drive Transcriptome-Proteome Alignment in a Minimal Photoautotroph

The cyanobacterium Prochlorococcus marinus MED4 is a minimal photoautotroph that maintains circadian regulation despite its reduced circadian regulatory toolkit relative to other cyanobacteria. Moreover, MED4, like other small prokaryotes, has low transcript counts per cell and poor transcriptome-proteome alignment. A systems-level understanding of how MED4 uses its minimal regulatory machinery to achieve a well-coordinated circadian cycle is currently lacking. We address this knowledge gap by analyzing global proteomics, transcriptomics, metabolomics, and lipidomics collected across a circadian day. Integrating these data with statistical analyses, enzyme-constrained metabolic modeling, and stochastic mathematical modeling allows us to reveal and characterize six major population-level cell states. Here we present evidence that high-light response regulator RpaB plays an important night-time regulatory role in MED4 by inhibiting RpaA, the master transcriptional activator of dusk genes and HimA, a regulatory target of RpaA previously shown to influence DNA conformation, is highly correlated with global transcriptome-proteome alignment (R2 = 0.67, p < 0.001). We construct stochastic differential equations consistent with genome-wide promotion of transcription by HimA as a plausible mechanism. Our HimA-driven model recapitulates alignment dynamics (R2 = 0.59, p < 0.01) as one plausible explanation. Collectively, our results elucidate how a minimal circadian regulatory program achieves robust coordination across transcriptional, translational, and metabolic levels

systems biology↗

bioRxiv2026

Cyanophage CP12 Rewires Host Carbon Regulation through Interface Remodeling and Redox Buffering

Picocyanobacteria drive ocean carbon fixation, and cyanophages reshape host metabolism during infection. In cyanobacteria, the intrinsically disorder Calvin cycle protein 12 (CP12) assembles glyceraldehyde-3-phosphate dehydrogenase (GAP2) and phosphoribulokinase (PRK) into the inhibitory dark complex, yet how phage CP12 homologs modulate redox-sensitive partners remains unclear. Here, we examined viral CP12 across sequence, structure, and post-translational modification (PTM) complexities to resolve the mechanistic remodeling of dark-complex assembly and regulation. Protein-family analysis of CP12 homologs across diverse lineages showed that viral CP12 preserves interface-dominated positions while shifting partner-facing chemistry toward charged and geometry-modulating features. Matched molecular dynamics simulations (MD) of Prochlorococcus MED4 and cyanophage P-HM2 showed that phage CP12 preserves assembly while strengthening PRK-facing contacts and reducing GAP2-facing interface burial. MED4 redox proteomics identified coordinated cysteine oxidation across CP12 and GAP2 under light disturbance, guiding MD to explore thiol-PTM states. Conformational divergence increased with PTM load and localized mainly to GAP2 modifications. Thiol PTM at GAP2 imposed the largest CP12 binding-energy cost, which P-HM2 CP12 buffered, yielding smaller comparative binding-energy penalties than host CP12. These findings link sequence-driven chemistry to interface dynamics and redox PTM responsiveness to light, defining phage CP12 as a regulatory mimetic that may retune host carbon regulation during infection.

microbiology↗

bioRxiv2026

Mitochondrial and protein homeostasis pathways are transcriptionally impaired in islets during type 1 diabetes pathogenesis

The decline in first-phase insulin response (FPIR) during the presymptomatic period of type 1 diabetes (T1D) is well established. In-situ functional studies with pancreas tissue slices showed that {beta}-cell loss of glucose-responsiveness was independent of T-cell infiltration into islets in recent-onset T1D cases. However, the mechanisms driving {beta}-cell dysfunction before the onset of T1D remain unclear. In pancreas tissue from donors across the natural history of T1D, we utilized an in-situ, whole-islet phenotypical and transcriptomic approach to unravel novel targets in the glucose-stimulus coupled secretion pathway that are similarly impaired in T-cell infiltrated and non-infiltrated islets. Specifically, we observed that islets from autoantibody positive (single(s) or multiple(m) AAb+) donors exhibited activation of post-transcriptional gene regulation along with reduced protein translation, processing in the endoplasmic reticulum (ER), and ER stress. Disrupted mitochondrial metabolism and bioenergetics were prominent in islets from multiple AAb+ and T1D donors with disease durations [≤]7 years. In addition, T1D islets presented reduced mitochondrial protein import, quality control, and dynamics, together with downregulated genes in insulin secretory pathways. During infiltration, these pathways remain dysregulated while immune/inflammatory transcripts were increased. These studies identified novel mechanisms of {beta}-cell dysregulation before symptomatic onset and independent of T-cell infiltration in T1D pathogenesis.

physiology↗

bioRxiv2026

Carbamylome analysis reveals regulatory roles for lysine carbamylation in β-cell glycolytic and insulin-processing enzymes

In type 1 diabetes (T1D), insulin-producing {beta} cells are destroyed by an autoimmune response driven by pro-inflammatory cytokines, including interferons. {beta}-cell cytokine signaling is mediated in part by post-translational modifications, such as phosphorylation and acetylation. However, the role of other post-translational modifications in {beta}-cell cytokine signaling represents an important knowledge gap. In the context of autoimmune diseases, lysine carbamylation has gained attention for its role in pathogenesis. Here, we investigate the role of carbamylation in T1D. We found that pancreatic islet cells from the T1D model, non-obese diabetic (NOD) mice, exhibit 11% carbamylation-positive cells, whereas non-diabetic CD1 mice have only 5%. Proteomics analysis of the MIN6 insulin-producing cell line treated with a cocktail of three pro-inflammatory cytokines IFN{gamma} + IL-1{beta} + TNF identified 284 carbamylated peptides from 222 proteins impacted by the cytokine treatment. Integration of carbamylation and acetylation provided a deep view of the cytokine-regulated PTMs and potential points of interplay. A functional-enrichment analysis revealed that carbamylation was enriched in pathways related to autoimmune diseases, metabolism, DNA replication, and protein translation. Moreover, functional testing demonstrated that carbamylation inhibits the glycolytic enzyme aldolase A and the insulin-processing enzyme carboxypeptidase E, identifying a possible role for cytokine-induced {beta}-cell dysfunction. In summary, protein carbamylation is elevated in islets from NOD mice, and pro-inflammatory cytokine treatment regulates protein carbamylation in MIN6 cells. These data identify carbamylation as a potential regulatory mechanism for {beta}-cell metabolism and insulin production in the context of islet inflammation.

biochemistry↗

bioRxiv2026

Extreme genome reduction selectively retains modular regulatory architecture in Prochlorococcus MED4: conserved transcriptional modules reveal core physiological regulatory programs

Prochlorococcus MED4 is a minimal photoautotroph whose extreme genome streamlining extends to its transcriptional regulatory architecture, yet it dominates high-light oligotrophic surface waters and drives marine carbon cycling. Despite ecological significance, MED4 remains genetically intractable, lacking molecular tools to characterize regulatory mechanisms and construct a transcriptome-wide regulatory map. To address this, we assembled an RNA-seq compendium of 253 samples, including 207 new samples capturing transcriptional responses across three classes of experiments: diverse environmental perturbations, a 24-hour circadian cycle, and phage infection. Using independent component analysis (ICA) applied to 247 quality-filtered samples, we identify 32 independently regulated gene set modules in MED4 (iModulons). By comparison, we previously identified 78 iModulons in the model cyanobacterium Synechococcus elongatus PCC 7942, revealing how dramatically genome reduction has simplified MED4s regulatory architecture. Of the 32 iModulons in MED4, 13 are conserved modules that correlate with experimentally validated transcriptional regulons in PCC 7942, identifying regulatory programs that resisted elimination under extreme selective pressure. These conserved modules reveal regulatory programs governing photosynthesis and light responses (RpaB), circadian rhythms (RpaA), and nutrient assimilation (NtcA, PhoB). Known regulator-specific DNA-binding motifs upstream of genes in conserved modules independently support their identification as regulatory targets. Notably, RpaA governs circadian rhythms through three temporally distinct modules in MED4 versus one in PCC 7942, and the RpaB photoprotection module similarly splits into two. This work uncovers the minimal regulatory core governing photosynthesis, circadian rhythms, and C/N/P metabolism in a globally critical but genetically intractable photoautotroph. This approach offers a generalizable framework for regulatory inference beyond model organisms. ImportanceThe minimal photoautotroph Prochlorococcus MED4 possesses only 28 transcriptional regulators, versus 150+ found in most cyanobacteria, reflecting a genome streamlined by billions of years of natural selection. This streamlining minimized metabolic costs, enabling MED4 to dominate nutrient-depleted oceans today. This raises a fundamental question: which regulatory programs did nature choose to keep? The answer matters, but MED4 cannot be studied by conventional genetics, placing its molecular machinery beyond direct experimental reach. Instead, we use large-scale computational methods to define groups of co-regulated genes in MED4. By comparing MED4 with a genetically tractable model cyanobacterium, we can distinguish which regulatory programs nature preserved from those it discarded. This work reveals the minimal regulatory architecture sufficient to sustain the smallest oxygenic photoautotroph on Earth. The principles uncovered here, distinguishing essential from dispensable regulatory programs in a naturally streamlined organism, inform the design of minimal photosynthetic platforms for biotechnology.

systems biology↗

bioRxiv2025

Single-Islet Proteomics Maps Pseudo-Temporal Islet Immune Responses and Dysfunction in Stage 1 Type 1 Diabetes

Progressive {beta}-cell dysfunction precedes the onset of type 1 diabetes (T1D), yet the molecular mechanisms driving early T1D development remain poorly understood. Although single-cell RNA-sequencing has uncovered transcript-level changes in human islet cells, it offers limited insight into the heterogeneity of distinct islet microenvironments. Here, we applied a single-islet proteomics workflow to profile intra-donor islet heterogeneity in three stage 1 T1D cases with matched non-diabetic controls and define in situ protein signatures of pseudo-temporal islet dysfunction. Intra-donor analyses of [~]100 individual islets per donor revealed highly consistent proteomic patterns reflecting pseudo-time progression of islet immune responses and {beta}-cell dysfunction. Several pathways, including extracellular matrix remodeling and mRNA processing, were identified as closely associated with progressive islet immune activation and loss of {beta}-cell function. These findings provide robust proteome-wide evidence of the progression of islet dysfunction, offer a valuable resource for investigating early mechanisms of T1D pathogenesis-- including novel candidates for functional studies--and underscore the utility of single-islet spatial proteomics for examining islet heterogeneity in T1D.

systems biology↗

bioRxiv2025

An Antibody Cocktail-Based Immunoaffinity-LC-MS Method Enabled Ultra-Sensitive and Robust Quantification of Circulating Proinsulin Proteoforms and C-peptide

Accurately measuring circulating proinsulin proteoforms is crucial for clinical investigation of diabetes, but was previously not feasible owing to limited assay specificity/sensitivity. Here we devised a highly sensitive LC-MS-based strategy to quantify intact proinsulin, des-31,32 and des-64,65 proinsulin, and C-peptide in circulation. The method involves: i)quantitative, robust affinity capture using an optimized antibody cocktail, eliminating the severe quantitative bias across multiple proteomes typically introduced when using a single antibody; ii)Lys-C digestion producing unique signature peptides for each proteoform, and iii)trapping-nano-LC coupled with FAIMS/dCV-MS for an ultra-sensitive analysis. The selective trapping/delivery ensured sensitive/selective analysis of the targets while achieving excellent analytical robustness that is critical for clinical assays, and the FAIMS/dCV substantially reduces baseline noise/interferences, further enhancing S/N. The assay achieved exceptional sensitivity, with serum LOQs of 1.7, 2.3, and 3.6 pg/mL respectively for intact-proinsulin, des-31,32 and des-64,65, representing the first assay capable of sensitively quantifying these major circulating proinsulin proteoforms. We applied this assay to 78 subjects, including autoantibody positive(n=20) and new-onset type-1-diabetes(T1D, n=19) with respective age/sex/BMI-matched controls, enabling the first accurate profiling of proinsulin proteoforms in clinical groups. The assay results demonstrated a clear separation of control and new-onset T1D groups that a parallel total-proinsulin ELISA assay fails to capture. Furthermore, distinct expression patterns in relative abundance ratios among proteoforms were observed across clinical groups. This assay may provide valuable insights into the {beta}-cell functions and the onset/progression of diabetes and other associated conditions. Moreover, the strategy is broadly applicable to targeted measurement of other biomarker proteoforms.

biochemistry↗

bioRxiv2024

Synergy and antagonism in a genome-scale model of metabolic hijacking by bacteriophage

Bacteriophage auxiliary metabolic genes (AMGs) alter host metabolism by hijacking reactions. Previous studies used functional annotations to infer AMG impacts but neglected propagation effects on global metabolism and phage production. We demonstrate the first integration of AMGs and phage assembly into a genome-scale metabolic model, using a general method applied to the infection of Prochloroccocus marinus MED4 by P-HM2. We experimentally validate our approach to predicting AMG impact on growth using cp12 mutations in Syne-chococcus elongatus. We predict that 17 directly hijacked reactions substantially impact over 30% of the metabolism, including carbon fixation, photosynthesis, and nucleotide synthesis. We find that indirect impacts are synergistically and antagonistically coupled and are either phage-aligned--shifting feasible reaction velocities in accordance with maximal phage production--or phage-antialigned. Pareto optimization reveals that phage-aligned reactions limit host growth, while phage-antialigned reactions do not. We provide systems-level insight into AMG perturbations, highlighting how nontrivial cascading effects shape microbial functions.

systems biology↗

bioRxiv2024

Increased Inflammation as well as Decreased Endoplasmic Reticulum Stress and Translation Differentiate Pancreatic Islets of Pre-symptomatic Stage 1 Type 1 Diabetes and Non-diabetic Cases

Aims/hypothesisProgression to type 1 diabetes (T1D) is associated with genetic factors, the presence of autoantibodies, and a decline in {beta} cell insulin secretion in response to glucose. Very little is known regarding the molecular changes that occur in human insulin-secreting {beta}-cells prior to the onset of T1D. Herein, we applied an unbiased proteomics approach to identify changes in proteins and potential mechanisms of islet dysfunction in islet autoantibody-positive organ donors with pre-symptomatic stage 1 T1D (HbA1c [≤] 6). We aimed to identify pathways in islets that are indicative of {beta}-cell dysfunction. MethodsMultiple islet sections were collected through laser microdissection of frozen pancreatic tissues of organ donors positive for islet autoantibodies (AAb+, n=5), compared to age/sex-matched nondiabetic controls (ND, n=5) obtained from the Network for Pancreatic Organ donors with Diabetes (nPOD). Islet sections were subjected to mass spectrometry-based proteomics and analyzed with label-free quantification followed by pathway and functional annotations. ResultsAnalyses resulted in [~]4,500 proteins identified with low false discovery rate (FDR) <1%, with 2,165 proteins reliably quantified in every islet sample. We observed large inter-donor variations that presented a challenge for statistical analysis of proteome changes between donor groups. We therefore focused on the three multiple AAb+ cases (mAAb+) with high genetic risk and their three matched controls for a final statistical analysis. Approximately 10% of the proteins (n=202) were significantly different between mAAb+ cases versus ND. The significant alterations clustered around major functions for upregulation in the immune response and glycolysis, and downregulation in endoplasmic reticulum (ER) stress response as well as protein translation and synthesis. The observed proteome changes were further supported by several independent published datasets, including proteomics dataset from in vitro proinflammatory cytokine-treated human islets and single cell RNA-seq data sets from AAb+ cases. Conclusion/interpretationIn-situ human islet proteome alterations at the stage 1 of AAb+ T1D centered around several major functional categories, including an expected increase in immune response genes (elevated antigen presentation / HLA), with decreases in protein synthesis and ER stress response, as well as compensatory metabolic response. The dataset serves as a proteomics resource for future studies on {beta} cell changes during T1D progression and pathogenesis.

pathology↗

bioRxiv2021

A comprehensive urine proteome database generated from patients with various renal conditions and prostate cancer

Urine proteins can serve as viable biomarkers for diagnosing and monitoring various diseases. A comprehensive urine proteome database, generated from a variety of urine samples with different disease conditions, can serve as a reference resource for facilitating discovery of potential urine protein biomarkers. Herein, we present a urine proteome database generated from multiple datasets using 2D LC-MS/MS proteome profiling of urine samples from healthy individuals (HI), renal transplant patients with acute rejection (AR) and stable graft (STA), patients with non-specific proteinuria (NS), and patients with prostate cancer (PC). A total of ~28,000 unique peptides spanning ~2,200 unique proteins were identified with a false discovery rate of <0.5% at the protein level. Over one third of the annotated proteins were plasma membrane proteins and another one third were extracellular proteins according to gene ontology analysis. Ingenuity Pathway Analysis of these proteins revealed 349 potential biomarkers. Surprisingly, 43% (167) of all known cluster of differentiation (CD) proteins were identified in the various human urine samples. Interestingly, following comparisons with five recently published urine proteome profiling studies, which applied similar approaches, there are still ~400 proteins which are unique to this current study. These may represent potential disease-associated proteins. Among them, several proteins such as myoglobin, serpin B3, renin receptor, and periostin have been reported as pathological markers for renal failure and prostate cancer, respectively. Taken together, our data should provide valuable information for future discovery and validation studies of urine protein biomarkers for various diseases.

systems biology↗