Biology subjects

Huang, T.

Publications and source records attributed to Huang, T..

At least 91 records · Page 5Linked to original sources

bioRxiv2023

The trade-off between individual metabolic specialization and versatility determines the metabolic efficiency of microbial communities

In microbial systems, a metabolic pathway can be either completed by one autonomous population or alternatively be distributed among a consortium performing metabolic division of labor (MDOL), where several specialized populations cooperate to complete the pathway. MDOL facilitates the systems function by reducing the metabolic burden; however, it may also hinder the function by reducing the exchange efficiency of metabolic intermediates among individuals. As a result, the metabolic efficiency of a community is influenced by trade-offs between the metabolic specialization and versatility of individuals, with the latter potentially introducing metabolic redundancy into the community. However, it remains unclear how metabolic specialization and versatility of the individuals involved can be controlled in order to optimize the function of the community. In this study, we deconstructed the metabolic pathway of naphthalene degradation into four specialized steps and introduced them individually or combinatorically into different strains, with varying levels of metabolic specialization. Using these strains, we engineered 1,456 synthetic consortia with varying levels of metabolic redundancy and tested their naphthalene degradation efficiency. We found that 74 consortia possessing metabolic redundancy exhibited higher degradation efficiency than both the autonomous population and the rigorous MDOL community. Quantitative modeling derived from our experiments provides general strategies for identifying the most effective MDOL consortium with functional redundancy (MCFR) from a range of possible MCFRs. Our large-scale genomic analysis suggests that natural communities for hydrocarbon degradation are mostly functionally redundant. In summary, our study provides critical insights into the engineering of high-performance microbial systems and explains why functional redundancy is prevalent in natural microbial communities.

microbiology↗

bioRxiv2023

Modification of social cheating facilitates the stabilization and chronic infection of polymorphic Pseudomonas aeruginosa population

Chronic infection of the common bacterial pathogen Pseudomonas aeruginosa frequently leads to the coexistence of heterogeneous individuals to engage in several group behaviors. However, further evolution of the polymorphic P. aeruginosa population, including the dynamic change of social cooperation and its impact on host immune system, still remain elusive. We show that the evolution of P. aeruginosa in the patients with chronic obstructive pulmonary disease frequently selects the isolates deficient in producing the costly and sharable extracellular products for nutrient acquisition. The evolution of polymorphic P. aeruginosa population is mainly concentrated on modifying the adaptability of lasR mutants, which are typical cheaters in the competition of quorum-sensing-controlled extracellular proteases. Importantly, lasR mutants with varying degrees of evolution interact with wild-type P. aeruginosa in a framework termed cascaded public goods game to compete for extracellular proteases and siderophores, and thus perpetuate social cooperation under different conditions. Finally, we find that a polymorphic population comprised of lasR-intact P. aeruginosa and evolved lasR-mutant can minimize the host immune fluctuation for persistent colonization. This study demonstrates the multistage evolution and complex interaction of P. aeruginosa in adaptation to host lungs, and provides an explanation for the success of cooperation in public goods game.

microbiology↗

bioRxiv2023

A rapid and sensitive multiplex, whole mount RNA fluorescence in situ hybridization and immunohistochemistry protocol

In the past few years, there has been an explosion in single-cell transcriptomics datasets, yet in vivo confirmation of these datasets is hampered in plants due to lack of robust validation methods. Likewise, modeling of plant development is hampered by paucity of spatial gene expression data. RNA fluorescence in situ hybridization (FISH) enables investigation of gene expression in the context of tissue type. Despite development of FISH methods for plants, easy and reliable whole mount FISH protocols have not yet been reported. We adapt a 3-day whole mount RNA-FISH method for plant species based on a combination of prior protocols that employs hybridization chain reaction (HCR), which amplifies the probe signal in an antibody-free manner. Our whole mount HCR RNA-FISH method shows expected spatial signals with low background for gene transcripts with known spatial expression patterns in Arabidopsis inflorescences and monocot roots. It allows simultaneous detection of three transcripts in 3D. We also show that HCR RNA-FISH can be combined with endogenous fluorescent protein detection and with our improved immunohistochemistry (IHC) protocol. The whole mount HCR RNA-FISH and IHC methods allow easy investigation of 3D spatial gene expression patterns in entire plant tissues.

molecular biology↗

bioRxiv2023

Variant-specific Mendelian Risk Prediction Model

Many pathogenic sequence variants (PSVs) have been associated with increased risk of cancers. Mendelian risk prediction models use Mendelian laws of inheritance to predict the probability of having a PSV based on family history, as well as specified PSV frequency and penetrance (agespecific probability of developing cancer given genotype). Most existing models assume penetrance is the same for any PSVs in a certain gene. However, for some genes (for example, BRCA1/2), cancer risk does vary by PSV. We propose an extension of Mendelian risk prediction models to relax the assumption that risk is the same for any PSVs in a certain gene by incorporating variant-specific penetrances and illustrating these extensions on two existing Mendelian risk prediction models, BRCAPRO and PanelPRO. Our proposed BRCAPRO-variant and PanelPRO-variant models incorporate variant-specific BRCA1/2 PSVs through the region classifications. Due to the sparsity of the variant information we classify BRCA1/2 PSVs into three regions; the breast cancer clustering region (BCCR), the ovarian cancer clustering region (OCCR), and an other region. Simulations were conducted to evaluate the performance of the proposed BRCAPRO-variant model compared to the existing BRCAPRO model which assumes the penetrance is the same for any PSVs in BRCA1 (and respectively BRCA2). Simulation results showed that the BRCAPRO-variant model was well calibrated to predict region-specific BRCA1/2 carrier status with high discrimination and accuracy on the region-specific level. In addition, we showed that the BRCAPRO-variant model achieved performance gains over the existing risk prediction models in terms of calibration without loss in discrimination and accuracy. We also evaluated the performance of the two proposed models, BRCAPRO-variant and PanelPRO-variant, on a cohort of 1,961 families from the Cancer Genetics Network (CGN). We showed that our proposed models provide region-specific PSV carrier probabilities with high accuracy, while the calibration, discrimination and accuracy of gene-specific PSV carrier probabilities were comparable to the existing gene-specific models. As more variant-specific PSV penetrances become available, we have shown that Mendelian risk prediction models can be extended to integrate the additional information, providing precise variant or region-specific PSV carrier probabilities and improving future cancer risk predictions.

genetics↗

bioRxiv2023

A compact model for cold tolerance entrainment based on the ICE1-CBF-COR pathway in plants

Most temperate plants can tolerate both chilling and freezing temperatures. Plants have developed self-defense mechanisms to perceive cold signal, trigger the cold tolerance for the cold response ICE1-CBF-COR pathway by packing a cascade of kinase phosphorylation/dephosphorylation events into a functional module. Linked to the central ICE1-CBF-COR model, two sub-models were adopted for the second messenSger Ca2+ -- a one-compartment model for Ca2+ transient and a two-compartment model for a train of Ca2+ spikes. Numerical simulation verified the expression patterns of the cold-induced genes as observed in Arabidopsis thaliana, Brassica napa and Solanum lycopersicum, including wild types and mutants. Moreover, the desensitization and resensitization of CBF3 and COR15A were displayed as well as the dynamics in the gradually decreasing temperature response to cold stress. The duration of cold tolerance was predicted for approximate 10 days. Interpreting and predicting the dynamical behaviors of the cold signaling pathway are valuable and time-saving for understanding mechanisms of cold acclimation. Author summaryIn higher organisms, CBF3 transcriptional level are output in a pulse and COR15A transcriptional level are maintained at a high homeostatic level to respond cold stress, which is determined by a complex set of regulatory mechanisms. Feedback loops from Ca2+ perception onto CaM, kinases, cold-acclimated genes in sequence, which have been experimentally reported, are thought to induce COR15A transcript accumulation under cold temperature exposure. The cold response pathway has been modeled based on a computational model. However, protein kinase cascades made the model relatively complicated and the cold-response gene COR15A was absent. Here, we develop a compact model with cold tolerance target gene COR15A. We show that this model could reproduce the temporal dynamics and characteristics of the core gene variables in different plants with wild type and mutant. Reduction of CaM proportion and augment of negative feedback control by ZAT12 in the model results in the desensitization of CBF3 and COR15A. Less than 24-hr warm treatment loses the ability of resensitization of CBF3 and COR15A after 14-day cold exposure. We further predict that the duration of cold tolerance is maintained at about 10 days in our model.

systems biology↗

bioRxiv2023

High immigration rates critical for establishing emigration-driven diversity in microbial communities

Unraveling the mechanisms governing the diversity of ecological communities is a central goal in ecology. While microbial dispersal (including the emigration and immigration process) constitutes an important ecological process, the coupling effects of dispersal and microbial competition in microbial diversity are poorly understood. Here, we investigated how microbial dispersal affects the diversity of microbial communities in the presence of inter-species competition, using a generalized Lotka-Volterra model in combination with experimental investigations. Our model shows that emigration reduces the diversity induced by immigration at low immigration rates. We surprisingly find that it increases the diversity of the community when the immigration rates cross a defined threshold, which we identified as Ineutral. We also found that at high immigration rates, emigration weakens the relative abundance of fast-growing species, and thus enhances the mass effect and increases the diversity. We experimentally confirmed this finding using cocultures of 20 bacterial strains isolated from the soil. Our model further showed that Ineutral exists over a wide range of species pool sizes, growth rates, and interspecies interactions, and decreases with the increasing of species pool size, growth rate, and interspecies interaction. Our work deepens the understanding of the effects of dispersal on diversity of natural communities.

ecology↗

bioRxiv2023

Exploration of the Link Between COVID-19 and Alcoholic Hepatitis from the Perspective of Bioinformatics and Systems Biology

ObjectiveSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been suggested to purpose threats to health of mankind. Alcoholic hepatitis (AH) is a life-threatening acute and chronic liver failure that takes place in sufferers who drink excessively. During the epidemic, AH has an increasing incidence of severe illness and mortality. However, for these two diseases, the intrinsic relationship of molecular pathogenesis, as well as common therapeutic strategies are still poorly understood. MethodsThe transcriptome of the COVID-19 and AH has been compared to obtain the altered genes and hub genes were screened out through protein-protein interaction (PPI) network analysis. Via gene ontology (GO), pathway enrichment and transcription regulator analysis, a deeper appreciation of the interplay mechanism between hub genes were established. ResultsWith 181 common differentially expressed genes (DEGs) of AH and COVID-19 were obtained, 10 hub genes were captured. Follow-up studies located that these 10 genes typically mediated the diseases occurrence by regulating the activities of the immune system. Other results suggest that the common pathways of the two ailments are enriched in regulating the function of immune cells and the release of immune molecules. ConclusionThis study reveals the common pathogenesis of COVID-19 and AH and assist to discover necessary therapeutic targets to combat the ongoing pandemic induced via SARS-CoV-2 infection and acquire promising remedy strategies for the two diseases.

bioinformatics↗

bioRxiv2023

The effect of Dnaaf5 gene dosage on primary ciliary dyskinesia phenotypes

DNAAF5 is a dynein motor assembly factor associated with the autosomal heterogenic recessive condition of motile cilia, primary ciliary dyskinesia (PCD). The effects of allele heterozygosity on motile cilia function are unknown. We used CRISPR-Cas9 genome editing in mice to recreate a human missense variant identified in patients with mild PCD and a second, frameshift null deletion in Dnaaf5. Litters with Dnaaf5 heteroallelic variants showed distinct missense and null gene dosage effects. Homozygosity for the null Dnaaf5 alleles was embryonic lethal. Compound heterozygous animals with the missense and null alleles showed severe disease manifesting as hydrocephalus and early lethality. However, animals homozygous for the missense mutation had improved survival, with partial preserved cilia function and motor assembly observed by ultrastructure analysis. Notably, the same variant alleles exhibited divergent cilia function across different multiciliated tissues. Proteomic analysis of isolated airway cilia from mutant mice revealed reduction in some axonemal regulatory and structural proteins not previously reported in DNAAF5 variants. While transcriptional analysis of mouse and human mutant cells showed increased expression of genes coding for axonemal proteins. Together, these findings suggest allele-specific and tissue-specific molecular requirements for cilia motor assembly that may affect disease phenotypes and clinical trajectory in motile ciliopathies. Brief SummaryA mouse model of human DNAAF5 primary ciliary dyskinesia variants reveals gene dosage effects of mutant alleles and tissue-specific molecular requirements for cilia motor assembly.

cell biology↗

bioRxiv2023

Bioinformatics Approaches to Determine the Effect of SARS-CoV-2 Infection on Patients with Intrahepatic Cholangiocarcinoma

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of coronavirus disease 2019 (COVID-19), has infected millions of individuals throughout the world, which poses a serious threat to human health. COVID-19 is a systemic disease that affects tissues and organs, including the lung and liver. Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are the most common liver cancer, and cancer patients are particularly at high risk of SARS-CoV-2 infection. The relationship between HCC and COVID-19 has been reported in previous studies, but ICC has been rare. With the methods of systems biology and bioinformatics, this study explored the link between COVID-19 and ICC. Transcriptional profiling of COVID-19 and ICC were obtained from the GEO database. A total of 70 common differentially expressed gene (DEGs) of both diseases were identified to investigate shared pathways. Then top-ranked 10 key DEGs (SCD, ACSL5, ACAT2, HSD17B4, ALDOA, ACSS1, ACADSB, CYP51A1, PSAT1, and HKDC1) were identified as hub genes by protein-protein interaction (PPI) network analysis. In addition, transcriptional regulatory networks regulating hub genes were revealed by hub Gene-transcription factor (TF) interaction analysis and hub gene-microRNA (miRNAs) interaction analysis. This study is expected to provide new references for future research and treatment of COVID-19 and ICC.

bioinformatics↗

bioRxiv2022

A stochastic world model on gravity for stability inference

The fact that objects without proper support will fall to the ground is not only a natural phenomenon, but also common sense in mind. Previous studies suggest that humans may infer objects stability through a world model that performs mental simulations with a priori knowledge of gravity acting upon the objects. Here we measured participants sensitivity to gravity to investigate how the world model works. We found that the world model on gravity was not a faithful replica of the physical laws, but instead encoded gravitys vertical direction as a Gaussian distribution. The world model with this stochastic feature fit nicely with participants subjective sense of objects stability and explained the illusion that taller objects are perceived as more likely to fall. Furthermore, a computational model with reinforcement learning revealed that the stochastic characteristic likely originated from experience-dependent comparisons between predictions formed by internal simulations and the realities observed in the external world, which illustrated the ecological advantage of stochastic representation in balancing accuracy and speed for efficient stability inference. The stochastic world model on gravity provides an example of how a priori knowledge of the physical world is implemented in mind that helps humans operate flexibly in open-ended environments. Significance StatementHumans possess an exceptional capacity for inferring the stability of objects, a skill that has been crucial to the survival of our predecessors and continues to facilitate our daily interactions with the natural world. The present study elucidates that our representation of gravitational direction adheres to a Gaussian distribution, with the vertical orientation as the maximum likelihood. This stochastic representation is likely to have originated from our interactions with the physical world, conferring an ecological advantage of balancing accuracy with speed. Therefore, the world model on gravity in the mind is a distorted replica of the natural world, enabling adaptive functionality in open-ended environments and thus shedding light on developing machines imbued with embodied intelligence.

neuroscience↗

bioRxiv2022

Cellular integration with a subretinal honeycomb-shaped prosthesis

In patients blinded by geographic atrophy, subretinal photovoltaic implant with 100{micro}m pixels provided visual acuity closely matching the pixel pitch. However, such flat bipolar pixels cannot be scaled below 75{micro}m, limiting the attainable visual acuity. This limitation can be overcome by shaping the electric field with 3-dimensional electrodes. In particular, elevating the return electrode on top of honeycomb-shaped vertical walls surrounding each pixel extends the electric field vertically and decouples its penetration into tissue from the pixel width. This approach relies on migration of the retinal cells into the honeycomb wells. Here, we demonstrate that the majority of the inner retinal neurons migrate into 25{micro}m deep wells, leaving the third-order neurons, such as amacrine and ganglion cells, outside. This is important for selective stimulation of the second-order neurons to preserve the retinal signal processing in prosthetic vision. Comparable glial response to that with flat implants suggests that migration and separation of the retinal cells by the walls does not cause additional stress. Furthermore, retinal migration into the honeycombs does not negatively affect its electrical excitability.

neuroscience↗

bioRxiv2022

Repurposing antihypertensive, lipid-lowering and antidiabetic drugs for lacunar stroke

BackgroundTo estimate the causal associations of modifiable risk factors with lacunar stroke (LS) and repurposing of common antihypertensive, lipid-lowering and antidiabetic drugs to prevent LS. MethodsThe effects of common antihypertensive, lipid-lowering and antidiabetic drugs on LS were estimated using a drug-target Mendelian randomization (MR) approach. LS data for the transethnic analysis were derived from meta-analyses comprising 7,338 cases and 254,798 controls. FindingsGenetically predicted hypertension and type 2 diabetes significantly increased LS risk. Elevated triglyceride and apolipoprotein B levels caused a 14% increased LS risk, while elevated apolipoprotein A-I and high-density lipoprotein levels caused a 12% decreased risk. Elevated triglyceride levels remained significantly associated with a higher LS risk in multivariable MR analysis (OR, 1.21; 95% CI, 1.06-1.40, P =0.005). Drug-target MR demonstrated that genetic variants mimicking calcium channel blockers most stably prevented LS (OR, 0.75; 95% CI, 0.61-0.92, P =0.006). The genetic variants at or near HMGCR (i.e., mimicking the effect of statins), NPC1L1 (mimicking the effects of ezetimibe) and APOC3 (mimicking antisense anti-apoC3 agents) were predicted to decrease LS incidence. Genetically proxied GLP1R agonism showed a marginal effect on LS, while a genetically proxied improvement in overall glycemic control was associated with a reduced LS risk (OR, 0.94; 95% CI, 0.92-0.96; P=4.58x10-7). InterpretationRepurposing several drugs with well-established safety and low costs for LS prevention in clinical practice may contribute to healthier brain aging. FundingThis study was supported by National Natural Science Foundation of China (grant numbers 8210051863).

genetics↗

bioRxiv2022

Enhancing Mitochondrial Functions by Optogenetic Clustering

Known as the powerhouses of cells, mitochondria and its dynamics are important for their functions in cells. Herein, an optogenetic method that controlling mitochondria to form the clusters was developed. The plasmid named CRY2PHR-mCherry-Miro1TM was designed for the optogenetic system. The photoactivable protein CRY2PHR was anchored to mitochondria, via the specific organelle-targeting transmembrane domain Miro1TM. Under blue light illumination, CRY2PHR can form the oligomerization, called puncta. With the illuminated time extended, the puncta can interact, and the mitochondria were found to form clustering with reversibility and spatiotemporal controllability. The mitochondrial functions were found to enhance after the formation of optogenetic mitochondrial clusters. This method presented here provides a way to control mitochondrial clustering and raise mitochondrial functions up.

cell biology↗

bioRxiv2022

Assigning functionality to cysteines by base editing of cancer dependency genes

Chemical probes are lacking for most human proteins. Covalent chemistry represents an attractive strategy for expanding the ligandability of the proteome, and chemical proteomics has revealed numerous electrophile-reactive cysteines on diverse proteins. Determining which of these covalent binding events impact protein function, however, remains challenging. Here, we describe a base-editing strategy to infer the functionality of cysteines by quantifying the impact of their missense mutation on cell proliferation. We show that the resulting atlas, which covers >13,800 cysteines on >1,750 cancer dependency proteins, correctly predicts the essentiality of cysteines targeted by cancer therapeutics and, when integrated with chemical proteomic data, identifies essential, ligandable cysteines on >110 cancer dependency proteins. We further demonstrate how measurements of reactivity in native versus denatured proteomes can discriminate essential cysteines amenable to chemical modification from those buried in protein structures, providing a valuable resource to prioritize the pursuit of small-molecule probes with high function-perturbing potential.

systems biology↗

bioRxiv2022

Firing rate adaptation in continuous attractor neural networks accounts for theta phase shift of hippocampal place cells

Hippocampal place cells in freely moving rodents display both theta phase precession and procession, which is thought to play important roles in cognition, but the neural mechanism for producing theta phase shift remains largely unknown. Here we show that firing rate adaptation within a continuous attractor neural network causes the neural activity bump to oscillate around the external input, resembling theta sweeps of decoded position during locomotion. These forward and backward sweeps naturally account for theta phase precession and procession of individual neurons, respectively. By tuning the adaptation strength, our model explains the difference between "bimodal cells" showing interleaved phase precession and procession, and "unimodal cells" in which phase precession predominates. Our model also explains the constant cycling of theta sweeps along different arms in a T-maze environment, the speed modulation of place cells firing frequency, and the continued phase shift after transient silencing of the hippocampus. We hope that this study will aid an understanding of the neural mechanism supporting theta phase coding in the brain.

neuroscience↗

bioRxiv2022

CD46 targeted 212Pb alpha particle radioimmunotherapy for prostate cancer treatment

We recently identified CD46 as a novel prostate cancer cell surface antigen that shows lineage independent expression in both adenocarcinoma and small cell neuroendocrine subtypes of metastatic castration resistant prostate cancer (mCRPC), discovered an internalizing human monoclonal antibody YS5 that binds to a tumor selective CD46 epitope, and developed a microtubule inhibitor-based antibody drug conjugate that is in a multi-center phase I trial for mCRPC (NCT03575819). Here we report the development of a novel CD46-targeted alpha therapy based on YS5. We conjugated 212Pb, an in vivo generator of alpha-emitting 212Bi and 212Po, to YS5 through the chelator TCMC to create the radioimmunoconjugate, 212Pb-TCMC-YS5. We characterized 212Pb-TCMC-YS5 in vitro and established a safe dose in vivo. We next studied therapeutic efficacy of a single dose of 212Pb-TCMC-YS5 using three prostate cancer small animal models: a subcutaneous mCRPC cell line-derived xenograft (CDX) model (subcu-CDX), an orthotopically grafted mCRPC CDX model (ortho-CDX), and a prostate cancer patient-derived xenograft model (PDX). In all three models, a single dose of 20 Ci 212Pb-TCMC-YS5 was well tolerated and caused potent and sustained inhibition of established tumors, with significant increases of survival in treated animals. A lower dose (10 Ci 212Pb-TCMC-YS5) was also studied on the PDX model, which also showed a significant effect on tumor growth inhibition and prolongation of animal survival. These results demonstrate that 212Pb-TCMC-YS5 has an excellent therapeutic window in preclinical models including PDXs, opening a direct path for clinical translation of this novel CD46-targeted alpha radioimmunotherapy for mCRPC treatment. SignificanceThis study reports a novel CD46 targeted 212Pb alpha particle radioimmunotherapy, 212Pb-TCMC-YS5, that is well tolerated and shows potent anti-tumor activity (tumor growth inhibition and increase of animal survival) in vivo in three prostate cancer small animal models, i.e., a subcutaneous and an intraprostate orthotopic mCRPC cell line-derived xenograft models, and a prostate cancer patient-derived xenograft model. Given that YS5 is a clinical stage human antibody, this YS5-based 212Pb alpha particle therapy has potential of translation to the clinic for treatment of mCRPC patients.

bioengineering↗

bioRxiv2022

Flaver: mining transcription factors in genome-wide transcriptome profiling data using weighted rank correlation statistics

BackgroundMining key transcription factors (TFs) in genome-wide transcriptome profiling data has been an active research area for many years and it has been partially solved by mathematically modelling the ranking orders of genes in the target gene-set for the TF of interest in the gene-list ranked by expression values, called gene-set enrichment analysis (GSEA). However, in some application scenarios the gene-set itself also has a rank attribute, such as the putative target gene-set predicted by the Grit software and other alternatives like FIMO and Pscan. New algorithms must be developed to analyze these data properly. Methodology/Principal FindingsBy implementing the weighted Kendalls tau statistic, we proposed a method for genome-wide transcriptome profiling data mining that can identify the key TFs orchestrating a profile. Theoretical properties of the proposed method were established, and its advantages over the GSEA approach were demonstrated when analyzing the RNA-Atlas datasets. The results showed that the top-rated TFs by our method always have experimentally supported evidences in the literatures. Benchmarking using gene ontology (GO) annotations in the AmiGO database indicated that the geometry performance (SQR_P) of our method is higher than GSEA in more than 14% of the cases. SignificanceThe developed method is suitable for analyzing the significance of overrepresentation of ranked gene-sets in a ranked gene-list. A software implementing the method, called "Flaver", was developed and is publicly available at http://www.thua45.cn/flaver under an academic free license. Author SummaryIdentification of the regulation roles of TFs in the transcriptome is fundamental in understanding various biological processes. Improve the performance of the prediction tools is important because accurate TF-mining in transcriptome data can finely improve the efficiency of wet-lab experiments. Also, genome wide TF-mining can provide new target genes for transcriptome regulation analysis in system biology perspective. This study developed a new TF-mining tool based on weighted rank correlation statistical method. The tool has better performance in analyzing ranked gene-set and ranked gene-list than its competitor, the GSEA tool. It can help the researchers in identification of the most important TFs in transcriptional data.

bioinformatics↗

bioRxiv2022

MSstatsPTM: Statistical relative quantification of post-translational modifications in bottom-up mass spectrometry-based proteomics

Liquid chromatography coupled with bottom up mass spectrometry (LC-MS/MS)-based proteomics is increasingly used to detect changes in post-translational modifications (PTMs) in samples from different conditions. Analysis of data from such experiments faces numerous statistical challenges. These include the low abundance of modified proteoforms, the small number of observed peptides that span modification sites, and confounding between changes in the abundance of PTM and the overall changes in the protein abundance. Therefore, statistical approaches for detecting differential PTM abundance must integrate all the available information pertaining to a PTM site, and consider all the relevant sources of confounding and variation. In this manuscript we propose such a statistical framework, which is versatile, accurate, and leads to reproducible results. The framework requires an experimental design, which quantifies, for each sample, both peptides with post-translational modifications and peptides from the same proteins with no modification sites. The proposed framework supports both label-free and tandem mass tag (TMT)-based LC-MS/MS acquisitions. The statistical methodology separately summarizes the abundances of peptides with and without the modification sites, by fitting separate linear mixed effects models appropriate for the experimental design. Next, model-based inferences regarding the PTM and the protein-level abundances are combined to account for the confounding between these two sources. Evaluations on computer simulations, a spike-in experiment with known ground truth, and three biological experiments with different organisms, modification types and data acquisition types demonstrate the improved fold change estimation and detection of differential PTM abundance, as compared to currently used approaches. The proposed framework is implemented in the free and open-source R/Bioconductor package MSstatsPTM.

bioinformatics↗