Biology subjects

Smith, L. M.

Publications and source records attributed to Smith, L. M..

40 records · Page 3Linked to original sources

bioRxiv2020

Precursor intensity-based label-free quantification software tools for proteomic and multi-omic analysis within the Galaxy Platform.

For mass spectrometry-based peptide and protein quantification, label-free quantification (LFQ) based on precursor mass peak (MS1) intensities is considered reliable due to its dynamic range, reproducibility, and accuracy. In LFQ workflows, protein abundance changes are inferred from peptide-level information, including microbial peptides (for metaproteomics) and peptides carrying post-translational modifications (for proteomics) and/or variant sequences (for proteogenomics). Multi-omics studies (such as proteogenomics and metaproteomics) rely on peptide detection and quantification to identify and quantify peptides that map to unique proteoforms and metaproteins. The Galaxy for proteomics (Galaxy-P) platform has proven useful for the development of accessible workflows to identify proteins in these complex multi-omic studies. However, proteomics workflows within the Galaxy platform have lacked well-tested label-free quantification tools. In this study, our main goals were to evaluate two recently published open-source LFQ tools and to implement them within the Galaxy platform, enabling their easy integration with established workflows. These two tools, moFF and FlashLFQ, were selected based on their described peptide quantification capabilities and amenability to Galaxy implementation. Through rigorous testing and communication with the tools developers, we gained insights into the software features necessary for maximizing the performance of each tool. Software features evaluated included: a) match-between-runs (MBR); b) using both Thermo .raw and HUPO standards .mzML file formats as input for improved quantification; c) use of containers and/or conda packages; d) parameters needed for analyzing large input datasets; and e) optimization and validation of software performance. This work 1) establishes a process for software implementation, optimization and validation within Galaxy; and 2) makes powerful new tools for LFQ available which should prove highly useful for a variety of proteomics and multi-omics applications employing the Galaxy platform.

bioinformatics↗

bioRxiv2018

Epigenome-wide Analysis Identifies Genes and Pathways Linked to Neurobehavioral Variation in Preterm Infants

Background & ObjectivesNeonatal neurobehavioral performance measures, such as the NICU Network Neurobehavioral Scale (NNNS), have been developed to assess the neurobehavioral characteristics of infants and provide insights into future developmental trajectories. The identification of molecular biomarkers of very early life neurobehavioral experiences could lead to better predictions of the long-term developmental outcomes of high-risk infants including preterm infants. To this end, we aimed to examine whether variability in DNA methylation (DNAm) or epigenetic age from surrogate tissues are associated with NNNS profiles in a cohort of infants born less than 30 weeks postmenstrual age (PMA).\n\nMethodsThis study was performed within the Neonatal Neurobehavior and Outcomes in Very Preterm Infants (NOVI) Study and included those infants with complete NNNS assessment data and DNAm measured from buccal cells, collected at near term-equivalent age using the Illumina EPIC array (N=536). We tested whether epigenetic age and age acceleration differed between infants based on their NNNS profile classifications. Then we performed an epigenome-wide association study, to test whether DNAm at individual epigenetic loci varied between these NNNS profile groupings. Models were adjusted for recruitment site, infant sex, postmenstrual age, and estimated tissue heterogeneity.\n\nResultsWe found that infants with an optimal NNNS profile had slightly older epigenetic age than other NOVI infants ({beta}1 = 0.201, p-value = 0.026), and that infants with an atypical NNNS profile had differential methylation at 29 CpG sites (FDR < 10%). The genes annotated to these differentially methylated CpGs included PLA2G4E, TRIM9, GRIK3, and MACROD2, which have previously been associated with neurological structure and function, or with neurobehavioral disorders.\n\nConclusionsGreater epigenetic age is associated with optimal NNNS responses while altered DNAm of multiple genes are associated with an atypical neurobehavioral profile at near-term equivalent age. These findings build upon the existing evidence that epigenetic variations in buccal cells may serve as markers of neonatal neurobehavior and might facilitate early identification of children at risk for abnormal developmental outcome.

epidemiology↗

bioRxiv2018

CrRLK1L receptor-like kinases HERK1 and ANJEA are female determinants of pollen tube reception

Communication between the gametophytes is vital for angiosperm fertilisation. Multiple CrRLK1L-type receptor kinases prevent premature pollen tube burst, while another CrRLK1L protein, FERONIA (FER), is required for pollen tube burst in the female gametophyte. We report here the identification of two additional CrRLK1L homologues, HERCULES RECEPTOR KINASE 1 (HERK1) and ANJEA (ANJ), which act redundantly to promote pollen tube burst at the synergid cells. HERK1 and ANJ localise to the filiform apparatus of the synergid cells in unfertilised ovules, and in herk1 anj mutants a majority of ovules remain unfertilised due to pollen tube overgrowth, together indicating that HERK1 and ANJ act as female determinants for fertilisation. As in fer mutants, the synergid cell-specific, endomembrane protein NORTIA (NTA) is not relocalised after pollen tube reception; however, unlike fer mutants, reactive oxygen species levels are unaffected in herk1 anj double mutants. Both ANJ and HERK1 associate with FER and its proposed co-receptor LORELEI (LRE) in planta. Together, our data indicate that HERK1 and ANJ act with FER to mediate female-male gametophyte interactions during plant fertilisation.

genetics↗

bioRxiv2018

Social Motility: Interaction between two sessile soil bacteria leads to emergence of surface motility

Bacteria often live in complex communities in which they interact with other organisms. Consideration of the social environment of bacteria can reveal emergent traits and behaviors that would be overlooked by studying bacteria in isolation. Here we characterize a social trait which emerges upon interaction between the distantly-related soil bacteria Pseudomonas fluorescens Pf0-1 and Pedobacter sp. V48. On hard agar, which is not permissive for motility of the mono-culture of either species, co-culture reveals an emergent phenotype we term interspecies social spreading, where the mixed colony spreads across the hard surface. We show that initiation of social spreading requires close association between the two species of bacteria. Both species remain associated throughout the spreading colony, with reproducible and non-homogenous patterns of distribution. The nutritional environment influences social spreading; no social behavior is observed under high nutrient conditions, but low nutrient conditions are insufficient to promote social spreading without high salt concentrations. This simple two-species consortium is a tractable model system that will facilitate mechanistic investigations of interspecies interactions and provide insight into emergent properties of interacting species. These studies will contribute to the broader knowledge of how bacterial interactions influence the functions of communities they inhabit.\n\nImportanceThe wealth of studies on microbial communities has revealed the complexity and dynamics of the composition of communities in many ecological settings. Fewer studies probe the functional interactions of the community members. Function of the community as a whole may not be fully revealed by characterizing the individuals. In our two-species model community, we find an emergent trait resulting from the interaction of the soil bacteria Pseudomonas fluorescens Pf0-1 and Pedobacter sp. V48. Observation of emergent traits suggests there may be many functions of a community that are not predicted based on a priori knowledge of the community members. These types of studies will provide a more holistic understanding of microbial communities, allowing us to connect information about community composition with behaviors determined by interspecific interactions. These studies increase our ability to understand communities, such as the soil microbiome, plant-root microbiome, and human gut microbiome, with the final goal of being able to manipulate and rationally improve these communities.

microbiology↗