Biology subjects

Huang, C.-C.

Publications and source records attributed to Huang, C.-C..

At least 19 recordsLinked to original sources

bioRxiv2026

Charting sex divergence in the human brain across the lifespan

Biological sex fundamentally shapes human brain organization, but sex-specific normative neuroanatomical trajectories across the lifespan remain largely uncharted. Here, we constructed independent, sex-specific lifespan brain charts using structural neuroimaging data from 59,915 healthy individuals (29,760 males and 30,155 females) ranging in age from 266 postconception days to 100 years. By examining 296 structural phenotypes across global, cortical, and subcortical measures, these models revealed widespread sex differences in maturational timing, with males reaching peak milestones later than females. These trajectories demonstrate that sex differences evolve dynamically, with phenotype-specific windows of emergence and maximal separation. Compared with conventional sex-pooled references, sex-specific models achieved superior predictive accuracy and reduced misestimation of individual deviations in healthy populations. Across five neuropsychiatric conditions, sex-specific models improved the detection of extreme deviations and revealed both shared and sex-dependent patterns of disorder-related neuroanatomical abnormalities. These sex-specific charts establish tailored normative references for assessing brain development, ageing, and disease.

neuroscience↗

bioRxiv2026

Nonequilibrium States Promote One-Pot Nonenzymatic Carbon Fixation in the Reverse Tricarboxylic Acid Cycle and Amino Acid Synthesis

Several metabolites within the reductive tricarboxylic acid (rTCA) cycle have been found to form prebiotically. However, how these metabolites connect to each other and form rTCA cycle remains unresolved. The rTCA cycle is an ancient route and is considered significant for the emergence of life, since it connects to the routes of amino acids and nucleobases synthesis. A major challenge to complete the rTCA cycle under prebiotic conditions is the thermodynamically unfavorable reductive carboxylation of succinate to -ketoglutarate. Here, we address this challenge by using the nature of energy: nonequilibrium conditions. By calculating the changes in free energy, {Delta}G, of succinate to -ketoglutarate, and its downstream reactions: -ketoglutarate to glutamate and -ketoglutarate to isocitrate under different nonequilibrium conditions, we find that these two-step reactions are exergonic under nonequilibrium conditions at a 10000:1 reactant-to-product ratio at 1.013 bar, pH 10 and 70{degrees}C. To prove the concept, we catalyze succinate to glutamate at a 10000:1 reactant-to-product ratio, with NH2OH and sodium dithionite. The process is catalyzed by Fe(0), Fe3O4, and artificial proto-[4Fe4S] clusters in 1M NaCl at pH 10 and 70{degrees}C under 1 atm of 13CO2 for 48 hours. This nonequilibrium condition and one-pot system successfully promote the formation of -ketoglutarate through carbon fixation with succinate and its subsequent conversion to glutamate. These findings demonstrate nonequilibrium states enable -ketoglutarate formation through succinate and CO2, and suggest that a tendency toward natural thermodynamics may serve as a driving force for autocatalysis in the origin of life. ImportanceHow life began remains open, metabolism provides a key framework for origins. We use a simple and robust energetic principle to show that non-equilibrium conditions can drive the highly endergonic carboxylation step of the reverse tricarboxylic acid (rTCA) cycle, enabling one-pot synthesis of glutamate. This is work bridges the gap between protometabolites and protometabolsim, suggesting that metabolites may have accumulated first, creating concentration gradients that drove reactions and ultimately enabled the emergence of protometabolism. These findings provide a plausible pathway from prebiotic chemistry to the emergence of metabolism.

biochemistry↗

bioRxiv2026

Single Cell-Type Spatial Proteomics Uncovers Regional Heterogeneity of Astrocytes

Astrocytes are a subset of glial cells in the central nervous system (CNS) that support numerous processes essential for brain function. Their functional diversity is thought to arise from specialized subpopulations with distinct molecular profiles. Although single-cell and single-nucleus RNA sequencing (scRNA-seq and snRNA-seq) have greatly advanced our understanding of astrocyte transcriptomic heterogeneity, mRNA abundance does not always correlate with protein levels because of post-transcriptional and translational regulation. Therefore, studying protein profiles remains essential to accurately capture astrocyte functional states and heterogeneity. Here, we used Microscoop Mint, a microscopy-guided spatial proteomics platform that integrates subcellular, region-specific sample preparation with LC-MS/MS-based mass spectrometry, enabling direct protein profiling of astrocytes in paraformaldehyde-fixed, optimal cutting temperature (OCT)-embedded mouse brain tissue. By applying this approach, we uncovered distinct regional-associated astrocyte proteomic signatures in the cerebral cortex and hippocampus and selected novel candidate protein markers for subsequent validation by immunofluorescence. Notably, MINK1 and PLEKHB1 showed preferential expression in hippocampal and cortical astrocytes, respectively, highlighting their potential as region-specific astrocyte markers. Overall, this strategy enables high-precision, unbiased spatial proteomic discovery at subcellular resolution, providing a powerful framework for linking molecular diversity to functional specialization in astrocyte biology.

neuroscience↗

bioRxiv2026

Development of autotrophy in Escherichia coli through adaptive laboratory evolution

Enabling heterotrophic Escherichia coli to use CO2 as its only carbon source remains a great challenge, and previous studies approached autotrophy conversion by metabolic engineering. Although its native carbon fixation routes were identified, the potential to reach autotrophy by itself has long been overlooked. In this study, autotrophy in E. coli was developed through adaptive laboratory evolution. After 1,000 days of consecutive inorganic subculturing, missense mutations were found in isocitrate dehydrogenase icd and isocitrate dehydrogenase kinase/phosphatase aceK genes, determining the metabolic switch between the citrate cycle and the glyoxylate shunt. By transcriptomic comparison of the adapted E. coli between inorganic and organic cultivations, two CO2 fixing enzymes activated in autotrophic mode were found, including the upregulated pyruvate:ferredoxin oxidoreductase YdbK and phosphoenolpyruvate carboxykinase Pck. Connected by the upregulated phosphoenolpyruvate synthase PpsA, a carbon fixation module was constituted, which was the shared foundation of the aspartate-threonine cycle and the citrate-glyoxylate-methylcitrate cycle, and thus integrating into an autotrophic network. By comparing the 13C enrichment patterns in inorganic cultivations between the adapted and initial E. coli, the favorable direction of the autotrophic network was confirmed. IMPORTANCEThis is the first study to accomplish autotrophy in E. coli through long-term evolution alone. Besides missense mutations in icd and aceK genes, adapted E. coli also actively regulated its gene expression to respond to inorganic environment, such as directing the metabolic switch towards the glyoxylate shunt. For biomass formation, a carbon fixation module consisted of the upregulated YdbK, PpsA, and Pck produced pyruvate and oxaloacetate as precursors for two cycles. The aspartate-threonine cycle with a replenishment side loop further accumulated these precursors, and the citrate-glyoxylate-methylcitrate cycle was driven by four overexpressed enzymes to catalyze six reactions. These metabolic pathways were integrated into a novel autotrophic network, and by understanding the nature of E. coli, rational designs for its carbon fixation optimization become attainable by using compatible mechanisms.

microbiology↗

bioRxiv2025

Association of GADD45A and favorable outcome in hormone positive breast cancer

BackgroundHormone receptor-positive (HR(+)) breast cancer is the most prevalent subtype in breast cancer, and although treatment options are rapidly increasing, still poses as an unmet need in advanced cases. Growth arrest and DNA damage-inducible alpha (GADD45A) is a gene with known relationship with the cell cycle and DNA damage pathways. Conflicting roles in breast cancer biology have been reported for GADD45A. In our study, we investigate the clinical and molecular association of GADD45A in HR(+) breast cancer, evaluating its prognostic potential and relationship with estrogen signaling. MethodsGADD45A expression was assessed in 100 breast cancer tissue samples from a tissue microarray and correlated with clinicopathologic parameters. Public genomic datasets were analyzed to validate associations between GADD45A expression and clinical outcomes in HR(+)HER2(-) breast cancer. Gene set enrichment analysis (GSEA) was used to investigate pathway correlations. ResultsGADD45A protein levels were highest in HR(+)HER2(-) tumors and positively correlated with estrogen receptor (ER) levels, consistent with a luminal phenotype. No significant association was observed between GADD45A levels and progression-free survival in CDK4/6 inhibitor-treated patients, suggesting limited predictive utility in this context. However, higher GADD45A expression was significantly associated with improved overall and relapse-free survival in HR(+)HER2(-) breast cancer in the METABRIC cohort, but not in HER2(+) or triple- negative subtypes. GSEA revealed a positive association between GADD45A expression and the estrogen late response signature, suggesting a functional link with hormone signaling. ConclusionGADD45A expression is enriched in luminal-type HR(+) breast cancer and correlates with favorable clinical outcomes. While not predictive of CDK4/6 inhibitor response, GADD45A may serve as a surrogate marker of estrogen signaling and improved prognosis. These findings support further investigation into GADD45A as a biomarker for stratification and potentially as a therapeutic target in HR(+) breast cancer.

cancer biology↗

bioRxiv2024

Endophytic pyrroloquinoline quinone enhances banana growth and immunity against Fusarium wilt for plant-microbe mutualisms

Fusarium wilt has a substantial impact on global banana production, posing a threat to food security worldwide. However, breeding new Fusarium-resistant cultivars is difficult and time-consuming. Alternatively, endophytic biostimulants that could combat such pervasive plant diseases provide possible novel solutions. Our prior research demonstrated that a pyrroloquinoline quinone (PQQ)-producing endophytic bacterium, Burkholderia seminalis 869T2, can enhance the growth of various plant species and protect bananas from Fusarium wilt in the field. PQQ is a peptide-derived redox cofactor known to stimulate mitochondrial biogenesis and metabolism in animals, but its molecular roles, especially in plants, remain to be elucidated. In this study, multi-omics approaches were employed to explore the potential mechanisms through which PQQ influences banana plants. The result of in situ imaging mass spectrometry revealed that the endophytic metabolite PQQ does not function through direct antagonism against Fusarium. The follow-up transcriptomic profiling shows it could regulate plant respiration, TCA cycle, oxidative phosphorylation, NAD/NADP-dependent dehydrogenases, MAPK signalling, and various phytohormone signalling pathways. Furthermore, PQQ appeared to trigger plant systemic immunity, thereby enhancing plant health and resistance to biotic stress. Beyond that, the complete genome of 869T2 was determined for follow-up comparative genomics analyses, revealing its genetic contexts, potential evolutionary events of PQQ operons among the Burkholderia species, and the absence of human virulence-facilitating genes within those PQQ-producing agricultural isolates. In summary, this study facilitates our understanding of PQQ in plant-microbe mutualisms and provides scientific evidence for its future application in agriculture. Significance StatementFusarium wilt is caused by Fusarium oxysporum f. sp. cubense tropical race 4 (Foc TR4), a notorious soil-borne pathogen that attacks bananas vascular system, which critically threatens global banana production and food security. A potential PQQ-producing endophytic strain has been confirmed to protect bananas through in planta biocontrol, reducing the morbidity of Banana Fusarium Wilt (BFW) disease in the field and promoting the growth of banana plants simultaneously. Our results revealed that the endophytic metabolite PQQ does not function through direct antagonism but triggers plant systemic immunity and coordinates energetic metabolisms, thereby improving the overall health of host plants and enhancing their resistance against Fusarium wilt.

plant biology↗

bioRxiv2024

Identify Regulatory eQTLs by Multiome Sequencing in Prostate Single Cells

While genome-wide association studies and expression quantitative trait loci (eQTL) analysis have made significant progress in identifying noncoding variants associated with prostate cancer risk and bulk tissue transcriptome changes, the regulatory effect of these genetic elements on gene expression remains largely unknown. Recent developments in single-cell sequencing have made it possible to perform ATAC-seq and RNA-seq profiling simultaneously to capture functional associations between chromatin accessibility and gene expression. In this study, we tested our hypothesis that this multiome single-cell approach allows for mapping regulatory elements and their target genes at prostate cancer risk loci. We applied a 10X Multiome ATAC + Gene Expression platform to encapsulate Tn5 transposase-tagged nuclei from multiple prostate cell lines for a total of 65,501 high quality single cells from RWPE1, RWPE2, PrEC, BPH1, DU145, PC3, 22Rv1 and LNCaP cell lines. To address data sparsity commonly seen in the single-cell sequencing, we performed targeted sequencing to enrich sequencing data at prostate cancer risk loci involving 2,730 candidate germline variants and 273 associated genes. Although not increasing the number of captured cells, the targeted multiome data did improve eQTL gene expression abundance by about 20% and chromatin accessibility abundance by about 5%. Based on this multiomic profiling, we further associated RNA expression alterations with chromatin accessibility of germline variants at single cell levels. Cross validation analysis showed high overlaps between the multiome associations and the bulk eQTL findings from GTEx prostate cohort. We found that about 20% of GTEx eQTLs were covered within the significant multiome associations (p-value [≤] 0.05, gene abundance percentage [≥] 5%), and roughly 10% of the multiome associations could be identified by significant GTEx eQTLs. We also analyzed accessible regions with available heterozygous SNP reads and observed more frequent association in genomic regions with allelically accessible variants (p = 0.0055). Among these findings were previously reported regulatory variants including rs60464856-RUVBL1 (multiome p-value = 0.0099 in BPH1) and rs7247241-SPINT2 (multiome p-value = 0.0002- 0.0004 in 22Rv1). We also functionally validated a new regulatory SNP and its target gene rs2474694-VPS53 (multiome p-value = 0.00956 in BPH1 and 0.00625 in DU145) by reporter assay and SILAC proteomics sequencing. Taken together, our data demonstrated the feasibility of the multiome single-cell approach for identifying regulatory SNPs and their regulated genes.

genetics↗

bioRxiv2023

Microscopy-guided subcellular proteomic discovery by high-speed ultra-content photo-biotinylation

Microscopy-guided proteomics at an organelle-dimension resolution is desired for revealing unknown protein constituents at specific disease- or functional-associated regions at the molecular-molecular interactions level. Here, we achieve protein spatial purification by introducing a firmware-integrated microscopy platform that triggers in situ subcellular photo-biotinylation of proteins at user-defined regions of interest (ROIs) one field of view (FOV) at a time for thousands of FOVs fully automatically. An illumination pattern at the analogous ROIs of each FOV is calculated on the fly by either machine learning or traditional image processing. Photoactivatable amino acid crosslinkers are activated by a two-photon focal light one spot at a time at a sub-millisecond illumination duration per spot. Imaging, pattern generation, targeted illumination, and FOV movement are coordinated and cycled with high-speed mechatronic control to complete illumination on millions of ROI spots within hours. Once enough proteins are biotinylated in a cell or tissue sample, the sample is scraped and lysed, and avidin pulldown is used to enrich proteins to achieve spatial protein scooping at a 240-nm precision. Subsequent LC-MS/MS is implemented to reveal the subcellular proteome in high sensitivity, specificity, and resolution. Using this technology termed optoproteomics, we have revealed novel stress granule-localized and amyloid {beta}-localized proteins validated by immunostaining. Together, spatial purification by ultra-content, high-speed microscopy-targeted photo-biotinylation enables unprecedented subcellular spatial proteomics discovery in any microscopically recognizable regions.

cell biology↗

bioRxiv2023

A cyclic dipeptide for salinity stress alleviation and the trophic flexibility of an endophyte reveal niches in salt marsh plant-microbe interactions

In response to climate change, the nature of endophytes and their applications in sustainable agriculture has attracted the attention of academia and agro-industries. We focused on the endophytic halophiles of the endangered Taiwanese salt marsh plant, Bolboschoenus planiculmis, and evaluated the functions of the isolates through in planta salinity stress alleviation assay using Arabidopsis. An endophytic strain Priestia megaterium BP01R2 that could promote plant growth and salinity tolerance was further characterised through multi-omics approaches. The transcriptomics results suggested that BP01R2 could function by tuning hormone signal transduction, energy-producing metabolism, multiple stress responses, etc. In addition, a cyclodipeptide, cyclo(L-Ala-Gly), identified by metabolomics analysis was later confirmed to contribute to salinity stress alleviation in stressed plants by exogenous supplementation. Here we provide a new perspective on host-microbe interactions in the wetland biome based on the multi-omics investigation and mixotrophic character of BP01R2. This study revealed a biostimulant-based plant-endophyte symbiosis with potential application in sustainable agriculture and facilitated our understanding of those enigmatic cross-kingdom relationships.

microbiology↗

bioRxiv2023

Functional connectome through the human life span

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimers disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.

neuroscience↗

bioRxiv2023

Modelling the displacement and coexistence of clonal lineages of Phytophthora infestans through revisiting past outbreaks

The continuous changes in the lineage proportions of populations in the clonal plant pathogen Phytophthora infestans on potato and tomato crops have been perplexing to researchers and disease managers. Sudden outbreaks of newly emergent genotypes are often associated with these rapid composition changes. Modelling can predict the persistence and displacement of pathogen genotypes with differential fitness among hosts. Building upon previous models, we combined analytical and simulation methods to model the outcome of interactions between competing lineages on multiple hosts. Model inputs include pathogenesis parameters, and the outputs are fitness and lineage proportions within each host. Analytical solutions yielding complete displacement, partial coexistence-displacement, and complete coexistence were described. In a retrospective study, the lesion growth rate and sporulation density of P. infestans lineages on potato and tomato from pathogenicity trials were used as inputs. Output lineage frequencies were compared with historical epidemiological situations to check model accuracy. The results showed that pathogenesis traits measured from empirical trials could simulate lineage constituents on potato and tomato, and estimate genotypic fitness with reasonable accuracy. The model also showed promise in predicting ongoing lineage displacements in the subsequent year or few years, even when the displaced lineage was still highly prevalent during the time of isolation. However, large uncertainties remain at temporal-spatial scales owing to complex meta-population dynamics in some regions and adaptation to local environmental factors. This simulation model provides a new tool for forecasting pathogen compositions, and can be used to identify potentially problematic genotypes based on pathogen life-history traits.

pathology↗

bioRxiv2023

Mapping Neurophysiological Subtypes of Major Depressive Disorder Using Normative Models of the Functional Connectome

Major depressive disorder (MDD) is the most burdensome psychiatric disorder characterized by remarkably heterogeneous clinical phenotypes. It remains challenging to delineate the heterogeneity of neurobiological abnormalities underlying the clinical variance and, on this basis, to identify neurophysiological subtypes of MDD patients. Here, using a large multisite resting-state functional MRI data from 1,148 MDD patients and 1,079 healthy controls, we generated lifespan normative models of functional connectivity strengths, mapped the heterogeneity of patients individual deviations, and identified neurobiological MDD subtypes. MDD patients showed positive deviations mainly in the default mode and subcortical areas, and negative deviations widely distributed over the cortex. However, there was a great inter-subject heterogeneity as indicated by that no more than 3.14% of patients deviated from the normative range for any brain region. Two neurophysiological MDD subtypes were identified. Subtype 1 showed severe deviations with positive deviations in the default mode, limbic, and subcortical areas, and negative deviations in the sensorimotor, dorsal and ventral attention areas, while subtype 2 showed a moderate but conversed deviation pattern. The severe-deviation subtype had older age, higher medicated proportion, and higher Suicide item score, while the moderate-deviation subtype showed higher Work and Activities and Depressed Mood item scores. Moreover, the baseline deviations in the severe-deviation subtype were predictive of 6-month antidepressant treatment effects in a subsample. To our knowledge, the current study is the largest multisite analysis of neurophysiological MDD subtyping to date and the findings shed light on our understanding of the biological mechanisms underlying the intersubject heterogeneity of clinical phenotypes, which are informative for the development of personalized treatments for this disorder.

neuroscience↗

bioRxiv2022

Integrated Diffusion Image Operator (iDIO): A tool for automated configuration and processing of diffusion MRI data

The preprocessing of diffusion magnetic resonance imaging (dMRI) data involves numerous steps, including the corrections for head motion, susceptibility distortion, low signal-to-noise ratio, and signal drifting. Researchers or clinical practitioners often need to configure different preprocessing steps depending on disparate image acquisition schemes, which increases the technical threshold for dMRI analysis for non-expert users. This could cause disparities in data processing approaches and thus hinder the comparability between studies. To make the dMRI data processing steps transparent and adapt to various dMRI acquisition schemes for researchers, we propose a semi-automated pipeline tool for dMRI named integrated Diffusion Image Operator or iDIO. This pipeline integrates features from a wide range of advanced dMRI software tools and targets at providing a one-click solution for dMRI data analysis, via automatic configuration for a set of optimal processing steps based on the image header of the input data. Additionally, the pipeline provides options for post-processing, such as estimation of diffusion tensor metrics and whole-brain tractography-based connectomes reconstruction using common brain atlases. The iDIO pipeline also outputs an easy-to-interpret quality control report to facilitate users to assess the data quality. To keep the transparency of data processing, the execution log and all the intermediate images produced in the iDIOs workflow are accessible. The goal of iDIO is to reduce the barriers for clinical or non-specialist users to adopt the state-of-art dMRI processing steps.

neuroscience↗

bioRxiv2021

Validating Pore Size Estimates in a Complex Microfibre Environment on a Human MRI System

PurposeRecent advances in diffusion-weighted MRI provide restricted diffusion signal fraction and restricting pore size estimates. Materials based on co-electrospun oriented hollow cylinders have been introduced to provide validation for such methods. This study extends this work, exploring accuracy and repeatability using an extended acquisition on a 300 mT/m gradient human MRI scanner, in substrates closely mimicking tissue, i.e., non-circular cross-sections, intra-voxel fibre crossing, intra-voxel distributions of pore-sizes and smaller pore-sizes overall. MethodsIn a single-blind experiment, diffusion-weighted data were collected from a biomimetic phantom on a 3T Connectom system using multiple gradient directions/diffusion times. Repeated scans established short-term and long-term repeatability. The total scan time (54 minutes) matched similar protocols used in human studies. The number of distinct fibre populations was estimated using spherical deconvolution, and median pore size estimated through the combination of CHARMED and AxCaliber3D framework. Diffusion-based estimates were compared with measurements derived from scanning electron microscopy. ResultsThe phantom contained substrates with different orientations, fibre configurations and pore size distributions. Irrespective of one or two populations within the voxel, the pore-size estimates (~5m) and orientation-estimates showed excellent agreement with the median values of pore-size derived from scanning electron microscope and phantom configuration. Measurement repeatability depended on substrate complexity, with lower values seen in samples containing crossing-fibres. Sample-level repeatability was found to be good. ConclusionWhile no phantom mimics tissue completely, this study takes a step closer to validating diffusion microstructure measurements for use in vivo by demonstrating the ability to quantify microgeometry in relatively complex configurations.

biophysics↗

bioRxiv2020

Dysglycemia is associated with Mycobacterium tuberculosis lineages in tuberculosis patients of North Lima - Peru.

This study was performed to investigate the role of dysglycemia on the genetic diversity of Mycobacterium tuberculosis (MTB) among pulmonary tuberculosis (TB) patients to build scientific evidence about the possible mechanisms of TB transmission. MTB isolates obtained of patients affected by pulmonary tuberculosis from health care facilities of North Lima - Peru, were analyzed using whole genome sequencing and 24-locus mycobacterial interspersed repetitive-unit-variable-number tandem repeats (MIRU-VNTR). Subsequently, clinical and epidemiological characteristics were associated with clustering, lineages and comorbid conditions. The analysis carried out 112 pulmonary TB patients from various health centers in North Lima, 17 (15%) had diabetes mellitus (DM) and 33 (29%) had pre-diabetes (PDM). Latin American-Mediterranean, Haarlem and Beijing were the most frequent MTB lineages found in those patients. Previous TB (adjusted odds ratio [aOR]=3.65; 95%CI: 1.32-17.81), age (aOR=1.12; 95%CI: 1.03-1.45) and Beijing lineage (aOR=3.53; 95%CI: 1.08-13.2) were associated with TB-DM comorbidity. Alcoholism (aOR=2.92; 95%CI: 1.10-8.28), age (aOR=1.05; 95%CI: 1.03-1.12) and Haarlem lineage (aOR=2.54; 95%CI: 1.04-6.51) were associated with TB-PDM comorbidity. Beijing and Haarlem lineages were independently associated with TB-DM and TB-PDM comorbidities, respectively. Although these findings may be surprising, we must be cautious to suggest that dysglycemia could be associated with a highly clustering and predisposition of MTB lineages related to a serious impact on the severity of TB disease, which requires further research.

molecular biology↗

bioRxiv2020

Differential patterns of gyral and sulcal morphological changes during normal aging process

The cerebral cortex is a highly convoluted structure with distinct morphologic features, namely the gyri and sulci, which are associated with the functional segregation or integration in the human brain. During the lifespan, the brain atrophy that is accompanied by cognitive decline is a well-accepted aging phenotype. However, the detailed patterns of cortical folding change during aging, especially the changing trajectories of gyri and sulci, which is essential to brain functioning, remain unclear. In this study, we investigated the morphology of the gyral and sulcal regions from pial and white matter surfaces using MR imaging data of 417 healthy participants across the lifespan (21-92y). To elucidate the age-related changes in the cortical pattern, we fitted cortical thickness and intrinsic curvature of gyri and sulci using the quadratic model to evaluate their trajectories during normal aging. Our findings show that comparing to gyri, the sulcal thinning is the most prominent pattern during the aging process, and the gyrification of pial and white matter surfaces were also affected differently, which implies the vulnerability of functional segregation during aging. Taken together, we propose a morphological model of aging that may provide a framework for understanding the mechanisms underlying the gray matter degeneration.

neuroscience↗

bioRxiv2020

Large-scale Gradient Dysfunction of the Functional Connectome in Major Depression

BackgroundPatients with major depressive disorder (MDD) exhibit concurrent deficits in sensory processing and high-order cognitive functions such as self-awareness and rumination. Connectome mapping studies have suggested a principal primary-to-transmodal gradient in functional brain networks, supporting the spectrum from sensation to cognition. However, whether this principal connectome gradient is disrupted in patients with MDD and how this disruption is associated with gene expression profiles remain unclear. MethodsUsing a large cohort of resting-state functional magnetic resonance imaging data from 2,234 participants (1,150 patients with MDD and 1,084 healthy controls) recruited at 10 sites, we investigated MDD-related alterations in the principal connectome gradient. We further used Neurosynth and postmortem gene expression data to assess the cognitive functions and transcriptional profiles related to the gradient alterations in MDD, respectively. ResultsRelative to controls, patients with MDD exhibited abnormal global topography of the principal primary-to-transmodal gradient, as indicated by reduced explanation ratio, gradient range, and gradient variation (Cohens d = -0.16[~]-0.21). Focal alterations of gradient scores were mostly in the primary systems involved in sensory processing and in the transmodal systems implicated in high-order cognition. The transcriptional profiles explained 53.9% of the spatial variance in the altered gradient patterns, with the most correlated genes enriched in transsynaptic signaling and calcium ion binding. ConclusionsThese results highlight the dysfunction of the core connectome hierarchy in MDD and its linkage with gene expression profiles, providing insights into the neurobiological and molecular genetic underpinnings of sensory-cognitive deficits in this disorder.

neuroscience↗

bioRxiv2020

Multimodal memory T cell profiling identifies a reduction in a polyfunctional Th17 state associated with tuberculosis progression

Mycobacterium tuberculosis (M.tb) results in 10 million active tuberculosis (TB) cases and 1.5 million deaths each year1, making it the worlds leading infectious cause of death2. Infection leads to either an asymptomatic latent state or TB disease. Memory T cells have been implicated in TB disease progression, but the specific cell states involved have not yet been delineated because of the limited scope of traditional profiling strategies. Furthermore, immune activation during infection confounds underlying differences in T cell state distributions that influence risk of progression. Here, we used a multimodal single-cell approach to integrate measurements of transcripts and 30 functionally relevant surface proteins to comprehensively define the memory T cell landscape at steady state (i.e., outside of active infection). We profiled 500,000 memory T cells from 259 Peruvians > 4.7 years after they had either latent M.tb infection or active disease and defined 31 distinct memory T cell states, including a CD4+CD26+CD161+CCR6+ effector memory state that was significantly reduced in patients who had developed active TB (OR = 0.80, 95% CI: 0.73-0.87, p = 1.21 x 10-6). This state was also polyfunctional; in ex vivo stimulation, it was enriched for IL-17 and IL-22 production, consistent with a Th17-skewed phenotype, but also had more capacity to produce IFN{gamma} than other CD161+CCR6+ Th17 cells. Additionally, in progressors, IL-17 and IL-22 production in this cell state was significantly lower than in non-progressors. Reduced abundance and function of this state may be an important factor in failure to control M.tb infection.

immunology↗