Biology subjects

Ma, A.

Publications and source records attributed to Ma, A..

7 recordsLinked to original sources

bioRxiv2018

The Dynamic Conformational Landscapes of the Protein Methyltransferase SETD8

Elucidating conformational heterogeneity of proteins is essential for understanding protein functions and developing exogenous ligands for chemical perturbation. While structural biology methods can provide atomic details of static protein structures, these approaches cannot in general resolve less populated, functionally relevant conformations and uncover conformational kinetics. Here we demonstrate a new paradigm for illuminating dynamic conformational landscapes of target proteins. SETD8 (Pr-SET7/SET8/KMT5A) is a biologically relevant protein lysine methyltransferase for in vivo monomethylation of histone H4 lysine 20 and nonhistone targets. Utilizing covalent chemical inhibitors and depleting native ligands to trap hidden high-energy conformational states, we obtained diverse novel X-ray structures of SETD8. These structures were used to seed massively distributed molecular simulations that generated six milliseconds of trajectory data of SETD8 in the presence or absence of its cofactor. We used an automated machine learning approach to reveal slow conformational motions and thus distinct conformational states of SETD8, and validated the resulting dynamic conformational landscapes with multiple biophysical methods. The resulting models provide unprecedented mechanistic insight into how protein dynamics plays a role in SAM binding and thus catalysis, and how this function can be modulated by diverse cancer-associated mutants. These findings set up the foundation for revealing enzymatic mechanisms and developing inhibitors in the context of conformational landscapes of target proteins.

biophysics↗

bioRxiv2018

QUBIC2: A novel biclustering algorithm for large-scale bulk RNA-sequencing and single-cell RNA-sequencing data analysis

The combination of biclustering and large-scale gene expression data holds a promising potential for inference of the condition specific functional pathways/networks. However, existing biclustering tools do not have satisfied performance on high-resolution RNA-sequencing (RNA-Seq) data, majorly due to the lack of (i) a consideration of high sparsity of RNA-Seq data, e.g., the massive zeros or lowly expressed genes in the data, especially for single-cell RNA-Seq (scRNA-Seq) data, and (ii) an understanding of the underlying transcriptional regulation signals of the observed gene expression values. Here we presented a novel biclustering algorithm namely QUBIC2, for the analysis of large-scale bulk RNA-Seq and scRNA-Seq data. Key novelties of the algorithm include (i) used a truncated model to handle the unreliable quantification of genes with low or moderate expression, (ii) adopted the mixture Gaussian distribution and an information-divergency objective function to capture shared transcriptional regulation signals among a set of genes, (iii) utilized a Core-Dual strategy to identify biclusters and optimize relevant parameters, and (iv) developed a size-based P-value framework to evaluate the statistical significances of all the identified biclusters. Our method validation on comprehensive data sets of bulk and single cell RNA-seq data suggests that QUBIC2 had superior performance in functional modules detection and cell type classification compared with the other five widely-used biclustering tools. In addition, the applications of temporal and spatial data demonstrated that QUBIC2 can derive meaningful biological information from scRNA-Seq data. The source code for QUBIC2 can be freely accessed at https://github.com/maqin2001/qubic2.

bioinformatics↗

bioRxiv2018

The genetics and genome-wide screening of perennialism loci in Zea diploperennis

Perennialism is common among the higher plants, yet we know little about its inheritance. To address this, six hybrids were made by reciprocally crossing perennial Zea diploperennis Iltis, Doebley & R. Guzman with three varieties/inbred lines of annual maize (Z. mays L. spp. mays). We specifically focused on the plants ability to regrow after flowering and senescence. All the F1 plants demonstrated senescence and regrowth for several cycles, indicating a dominant effect of the Z. diploperennis alleles. The regrowth ability was stably transmitted to progeny of the hybrids in segregation ratios that suggested the trait was controlled by two dominant, complementary loci. Genome-wide screening with genotyping-by-sequencing (GBS) identified two major regrowth loci reg1 and reg2 on chromosomes 2 and 7, respectively. GBS results were validated using a larger F2 population and PCR markers derived from the single nucleotide polymorphisms within the locus intervals. These markers will be employed to select near-isogenic lines for the two loci and to identify candidate genes in the loci in Z. diploperennis.\n\nSignificance StatementOur study contributes to our general understanding of inheritance of perennialism in the higher plants. Previous genetic studies of the perennialism in Zea have yielded contradictory results. We take a reductionist approach by specifically focusing on the plants ability to regenerate new shoots after senescence without regard to associated traits, such as rhizome formation, tillering or environmental impacts. Using this criterion, inheritance of perennialism in Zea appears to be dominantly and qualitatively inherited. Importantly, our data indicate that there is no major barrier to transferring this trait into maize or other grass crops for perennial crop development, which enhances sustainability of grain crop production in an environmentally friendly way.

plant biology↗

bioRxiv2018

OTUB1 non-catalytically regulates the stability of the E2 ubiquitin conjugating enzyme UBE2E1

OTUB1 is a deubiquitinating enzyme that cleaves K48-linked polyubiquitin chains and also regulates ubiquitin signaling through a unique, non-catalytic mechanism. OTUB1 binds to a subset of E2 ubiquitin conjugating enzymes and inhibits their activity by trapping the E2~ubiquitin thioester and preventing ubiquitin transfer. The same set of E2s stimulate the deubiquitinating activity of OTUB1 when the E2 is not charged with ubiquitin. Previous studies have shown that, in cells, OTUB1 binds to members of the UBE2D (UBCH5) and UBE2E families, as well as to UBC13 (UBE2N). Cellular roles have been identified for the interaction of OTUB1 with UBC13 and members of the UBE2D family, but not for UBE2E E2 enzymes. We report here a novel role for OTUB1-E2 interactions in modulating E2 protein ubiquitination. We find that depletion of OTUB1 dramatically destabilizes the E2 conjugating enzyme UBE2E1 (UBE2E1) in cells and that this effect is independent of the catalytic activity of OTUB1 but depends on the ability of OTUB1 to bind to UBE2E1. We show that OTUB1 suppresses UBE2E1 autoubiquitination in vitro and in cells, thereby preventing UBE2E1 from being targeted to the proteasome for degradation. Taken together, we have found a new role for OTUB1 in rescuing specific E2s from degradation in vivo.

cell biology↗

bioRxiv2018

Stable networks of water-mediated interactions are conserved in activation of diverse GPCRs

G protein-coupled receptors (GPCRs) have evolved to recognize incredibly diverse extracellular ligands while sharing a common architecture and structurally conserved intracellular signaling partners. It remains unclear how binding of diverse ligands brings about GPCR activation, the common structural change that enables intracellular signaling. Here, we identify highly conserved networks of water-mediated interactions that play a central role in activation. Using atomic-level simulations of diverse GPCRs, we show that most of the water molecules in GPCR crystal structures are highly mobile. Several water molecules near the G protein-coupling interface, however, are stable. These water molecules form two kinds of polar networks that are conserved across diverse GPCRs: (i) a network that is maintained across the inactive and the active states and (ii) a network that rearranges upon activation. Comparative analysis of GPCR crystal structures independently confirms the striking conservation of water-mediated interaction networks. These conserved water-mediated interactions near the G protein-coupling region, along with diverse water-mediated interactions with extracellular ligands, have direct implications for structure-based drug design and GPCR engineering.

biophysics↗

bioRxiv2018

A structural mechano-chemical model for dynamic instability of microtubule

Microtubules are a major component of the cytoskeleton and vital to numerous cellular processes. The central dogma of microtubules is that all their functions are driven by dynamic instability; understanding its key phenomena (i.e. catastrophe, rescue, pause, differential behaviors at the plus and minus ends) distilled from a myriad of experiments under a consistent and unified scheme, however, has been unattainable. Here, we present a novel statistical-physics-based model uniquely constructed from conformational states deduced from existing tubulin structures, with transitions between them controlled by steric constraints and mechanical energy of the microtubule lattice. This mechano-chemical model allows, for the first time, all the key phenomena of dynamic instability to be coherently reproduced by the corresponding kinetic simulations. Long-puzzling phenomena, such as aging, small GTP-cap size, fast catastrophe upon dilution and temperature-induced ribbon-to-tube transition of GMPCPP-tubulins, robustly emerge and thus can be understood with confidence.

cell biology↗

bioRxiv2018

Computational elucidation of regulatory network responding to acid stress in Lactococcus lactis MG1363

Acid stress caused by lactate increment can lead to the growth inhibition of bacteria and yes has not been fully defined. Regulons, serve as co-regulated gene groups contribute to the transcriptional regulation of microbe genome, have the potential in understanding the underlying regulatory mechanism. Lactococcus lactis is one of the most important Gram-positive lactic acid-producing bacteria, widely used in food industry and has been proved to have advantages in oral delivery of drug and vaccine. In this study, we designed a novel computational pipeline, RECTA, for regulon prediction. The pipeline carried out differentially expressed gene prediction, gene co-expression analysis, cis-regulatory motif finding, and comparative genomic study to predict and validate regulons related to acid stress response in Lactococcus lactis MG1363. A total of 51 regulons were identified, and 14 of them have computational verified significance. Among these 14 regulons, five of them were computationally predicted to be connected with acid stress response with (i) known transcriptional factors in MEME suite database successfully mapped in Lactococcus lactis MG1363; and (ii) differentially expressed genes between pH values of 6.5 (control) and 5.1 (treatment). Validated by 36 literature confirmed acid stress response related proteins and genes, 33 genes in Lactococcus lactis MG1363 were found having orthologous genes using BLAST, associated to six regulons. An acid response related regulatory network was constructed, involving two trans-membrane proteins, eight regulons (llrA, llrC, hllA, ccpA, NHP6A, rcfB, regulons #8 and #39), nine functional modules, and 33 genes with orthologous genes known to be associated to acid stress. Our RECTA pipeline provides an effective way to construct a reliable gene regulatory network based on regulon elucidation. The predicted resistance pathways could serve as promising candidates for better acid tolerance engineering in Lactococcus lactis. It has a strong application power and can be effectively applied to other bacterial genomes, where the elucidation of the transcriptional regulation network is needed.

systems biology↗