Biology subjects

Parker, B.

Publications and source records attributed to Parker, B..

25 records · Page 2Linked to original sources

bioRxiv2021

Iron-dependent mutualism between Chlorella sorokiniana and Ralstonia pickettii forms the basis for a sustainable bioremediation system

Mutualism between microalgae and bacteria is ubiquitous, but remains underexplored as a basis for biodegradation of anthropogenic pollutants. In industrial systems, poor iron uptake by microalgae limits growth, bioprocessing efficacy, and bioremediation potential. Iron supplementation is costly and ineffective because iron remains insoluble in aqueous medium and biologically unavailable. In aquatic environments, microalgae develop an association with bacteria that solubilize iron by production of siderophore, which increases the bioavailability of iron as a public good. Algae, in exchange, provides dissolved organic matter to bacteria to sustain such interkingdom associations. Therefore, using a case study of azo dye degradation, we combine environmental isolations and synthetic ecology as a workflow, establishing a microbial community to degrade industrially relevant Acid Black 1 dye. We create a mutualism between previously non-associated chlorophyte alga Chlorella sorokiniana and siderophore-producing bacterium Ralstonia pickettii, based on the eco-evolutionary principle of exchange of iron and carbon. This siderophore-mediated increased iron bioavailability increases reductive iron uptake, growth rate, and azoreductase-mediated dye degradation of microalga. In exchange, C. sorokiniana produces galactose, glucose, and mannose as major extracellular monosaccharides, supporting bacterial growth. We propose a mechanism whereby extracellular ferrireductase is crucial for azoreductase-mediated dye degradation in microalgae. Our work demonstrates that bioavailability of iron, which is often overlooked in industrial bio-designs, governs microalgal growth and enzymatic processes. Our results suggest that algal-bacterial consortia based on the active association are a self-sustainable mechanism to overcome existing challenges of micronutrient availability in bioremediation systems and their industrial translation.

microbiology↗

bioRxiv2021

SnapKin: a snapshot deep learning ensemble for kinase-substrate prediction from phosphoproteomics data

Mass spectrometry (MS)-based phosphoproteomics enables the quantification of proteome-wide phosphorylation in cells and tissues. A major challenge in MS-based phosphoproteomics lies in identifying the substrates of kinases, as currently only a small fraction of substrates identified can be confidently linked with a known kinase. By leveraging large-scale phosphoproteomics data, machine learning has become an increasingly popular approach for computationally predicting substrates of kinases. However, the small number of high-quality experimentally validated kinase substrates (true positive) and the high data noise in many phosphoproteomics datasets together impact the performance of existing approaches. Here, we aim to develop advanced kinase-substrate prediction methods to address these challenges. Using a collection of seven large phosphoproteomics datasets, including six published datasets and a new muscle differentiation dataset, and both traditional and deep learning models, we first demonstrate that a pseudo-positive learning strategy for alleviating small sample size is effective at improving model predictive performance. We next show that a data re-sampling based ensemble learning strategy is useful for improving model stability while further enhancing prediction. Lastly, we introduce an ensemble deep learning model ( SnapKin) incorporating the above two learning strategies into a snapshot ensemble learning algorithm. We demonstrate that the SnapKin model achieves overall the best performance in kinase-substrate prediction. Together, we propose SnapKin as a promising approach for predicting substrates of kinases from large-scale phosphoproteomics data. SnapKin is freely available at https://github.com/PYangLab/SnapKin.

bioinformatics↗

bioRxiv2020

Robust SARS-CoV-2-specific T-cell immunity is maintained at 6 months following primary infection

The immune response to SARS-CoV-2 is critical in both controlling primary infection and preventing re-infection. However, there is concern that immune responses following natural infection may not be sustained and that this may predispose to recurrent infection. We analysed the magnitude and phenotype of the SARS-CoV-2 cellular immune response in 100 donors at six months following primary infection and related this to the profile of antibody level against spike, nucleoprotein and RBD over the previous six months. T-cell immune responses to SARS-CoV-2 were present by ELISPOT and/or ICS analysis in all donors and are characterised by predominant CD4+ T cell responses with strong IL-2 cytokine expression. Median T-cell responses were 50% higher in donors who had experienced an initial symptomatic infection indicating that the severity of primary infection establishes a setpoint for cellular immunity that lasts for at least 6 months. The T-cell responses to both spike and nucleoprotein/membrane proteins were strongly correlated with the peak antibody level against each protein. The rate of decline in antibody level varied between individuals and higher levels of nucleoprotein-specific T cells were associated with preservation of NP-specific antibody level although no such correlation was observed in relation to spike-specific responses. In conclusion, our data are reassuring that functional SARS-CoV-2-specific T-cell responses are retained at six months following infection although the magnitude of this response is related to the clinical features of primary infection.

immunology↗

bioRxiv2018

LiF-MS: Mapping unstructured peptide-protein interactions using Ligand-Footprinting Mass Spectrometry

Unstructured peptides, or linear motifs, present a poorly understood molecular language within the context of cellular signaling. These modular regions are often short, unstructured and interact weakly and transiently with folded target proteins. Thus, they are difficult to study with conventional structural biology methods. We present Ligand-Footprinting Mass Spectrometry, or LiF-MS, as a method of mapping the binding sites and dynamic disorder of these peptides on folded protein domains. LiF-MS uses a cleavable crosslinker to mark regions of a protein contacted by a bound linear motif. We demonstrate this method can detect both conformation ensembles and binding orientations of a linear motif in its binding pocket to amino-acid-level detail. Furthermore, marked amino acids can be used as constraints in peptide-protein docking simulations to improve model quality. In conclusion, LiF-MS proves a simple and novel method of elucidating peptide docking structural data not accessible by other methods in the context of a purified system.

biochemistry↗

bioRxiv2018

Mob-family kinase co-activators bind cognate Ndr/Lats kinases through conserved and modular interface

Ndr/Lats kinases bind to Mob coactivator proteins and their complexes play important roles in \"Hippo\" signaling pathways controlling cell proliferation and morphogenesis. All Ndr/Lats kinases have a 70-80 amino acid long unique N-terminal region (NTR) which binds to Mob factors. In order to gain insight into the structural basis of kinase-coactivator binding specificity, we have determined the crystal structure of Cbk1(NTR)-Mob2 and Dbf2(NTR)-Mob1 complexes from yeast (S. cerevisiae). We show that the Ndr/Lats(NTR)-Mob interface is a common structural platform through which kinase-cofactor binding is mediated, albeit amino acid variations in key positions contribute to subgroup and organism-specific differences. We further show that conserved residues at the NTR-Mob interface may participate in novel activation mechanisms likely ubiquitous in Ndr/Lats kinases. Ndr/Lats kinase activation may resemble to that of other AGC kinases but with an extra structural requirement for NTR mediated Mob binding for proper allosteric activation.

biochemistry↗

bioRxiv2018

Quantifying multi-layered expression regulation in response to stress of the endoplasmic reticulum

The mammalian response to endoplasmic reticulum (ER) stress dynamically affects all layers of gene expression regulation. We quantified transcript and protein abundance along with footprints of ribosomes and non-ribosomal proteins for thousands of genes in cervical cancer cells responding to treatment with tunicamycin or hydrogen peroxide over an eight hour time course. We identify shared and stress-specific significant regulatory events at the transcriptional and post-transcriptional level and at different phases of the experiment. ER stress regulators increase transcription and translation at different times supporting an adaptive response. ER stress also induces translation of genes from serine biosynthesis and one-carbon metabolism indicating a shift in energy production. Discordant regulation of DNA repair genes suggests transcriptional priming in which delayed translation fine-tunes the early change in the transcriptome. Finally, case studies on stress-dependent alternative splicing and protein-mRNA binding demonstrate the ability of this resource to generate hypotheses for new regulatory mechanisms.

systems biology↗

bioRxiv2017

The cost of enforcing marine protected areas to achieve ecological targets

Protected areas are the primary management tool for conserving ecosystems, yet their intended outcomes may often be compromised by poaching. Consequently, many protected areas are ineffective paper parks that contribute little towards conserving ecosystems. Poaching can be prevented through enforcement and engaging with community members so they support protected areas. It is not clear how much needs to be spent on enforcement and engagement to ensure they are frequent enough to be effective at conserving biodiversity. We develop models of enforcement against illegal fishing in marine protected areas. We apply the models to data on fishing rates and fish biomass from a marine protected area in Raja Ampat, Indonesia and explore how frequent enforcement patrols need to be to achieve targets for coral reef fish biomass. Achieving pristine levels of reef fish biomass required almost year-round enforcement of the protected area. Surveillance of the protected area may also be enhanced if local fishers who support the reserve report on poaching. The opportunity for local fishing boats to participate in surveillance was too small for it to have much benefit for total reef fish biomass, which increases slowly. However, specific functional groups of fish have much higher population growth rates and their biomass was predicted to increase markedly with community surveillance. We conclude that budgets for park management must balance the cost of conducting frequent patrols against supporting alternative activities, like education to build community support. Optimized budgets will be much more likely to achieve ecological targets for recovering fish biomasses and will contribute to fiscal sustainability of protected areas.

ecology↗