Biology subjects

Smith, T.

Publications and source records attributed to Smith, T..

6 recordsLinked to original sources

bioRxiv2018

Structural basis for independent origins of new catalytic machineries in plant AAAD proteins

Radiation of the plant pyridoxal 5-phosphate (PLP)-dependent aromatic L-amino acid decarboxylase (AAAD) family has yielded an array of paralogous enzymes exhibiting divergent substrate preferences and catalytic mechanisms. Plant AAADs catalyze either the decarboxylation or decarboxylation-dependent oxidative deamination of aromatic L-amino acids to produce aromatic monoamines or aromatic acetaldehydes, respectively. These compounds serve as key precursors for the biosynthesis of several important classes of plant natural products, including indole alkaloids, benzylisoquinoline alkaloids, hydroxycinnamic acid amides, phenylacetaldehyde-derived floral volatiles, and tyrosol derivatives. Here, we present the crystal structures of four functionally distinct plant AAAD paralogs. Through structural and functional analyses, we identify variable structural features of the substrate-binding pocket that underlie the divergent evolution of substrate selectivity toward indole, phenyl, or hydroxyphenyl amino acids in plant AAADs. Moreover, we describe two mechanistic classes of independently arising mutations in AAAD paralogs leading to the convergent evolution of the derived aldehyde synthase activity. Applying knowledge learned from this study, we successfully engineered a shortened benzylisoquinoline alkaloid pathway to produce (S)-norcoclaurine in yeast. This work highlights the pliability of the AAAD fold that allows change of substrate selectivity and access to alternative catalytic mechanisms with only a few mutations. SignificancePlants biosynthesize their own proteinogenic aromatic L-amino acids, namely L-phenylalanine, L-tyrosine and L-tryptophan, not only for building proteins but also for the production of a plethora of aromatic-amino-acid-derived natural products. Pyridoxal 5-phosphate (PLP)-dependent aromatic L-amino acid decarboxylase (AAAD) family enzymes play important roles in channeling various aromatic L-amino acids into diverse downstream specialized metabolic pathways. Through comparative structural analysis of four functionally divergent plant AAAD proteins together with biochemical characterization and molecular dynamics simulations, we reveal the structural and mechanistic basis for the rich divergent and convergent evolutionary development within the plant AAAD family. Knowledge learned from this study aids our ability to engineer high-value aromatic-L-amino-acid-derived natural product biosynthesis in heterologous chassis organisms.

biochemistry↗

bioRxiv2018

Unbiased dynamic characterization of RNA-protein interactions by OOPS

Current methods for the identification of RNA-protein interactions require a quantity and quality of sample that hinders their application, especially for dynamic biological systems or when sample material is limiting. Here, we present a new approach to enrich RNA-Binding Proteins (RBPs): Orthogonal Organic Phase Separation (OOPS), which is compatible with downstream proteomics and RNA sequencing. OOPS enables recovery of RBPs and free protein, or protein-bound RNA and free RNA, from a single sample in an unbiased manner. By applying OOPS to human cell lines, we extract the majority of known RBPs, and importantly identify additional novel RBPs, including those from previously under-represented cellular compartments. The high yield and unbiased nature of OOPS facilitates its application in both dynamic and inaccessible systems. Thus, we have identified changes in RNA-protein interactions in mammalian cells following nocodazole cell-cycle arrest, and defined the first bacterial RNA-interactome. Overall, OOPS provides an easy-to-use and flexible technique that opens new opportunities to characterize RNA-protein interactions and explore their dynamic behaviour.

cell biology↗

bioRxiv2017

Barriers to Integration of Bioinformatics into Undergraduate Life Sciences Education

Bioinformatics, a discipline that combines aspects of biology, statistics, and computer science, is increasingly important for biological research. However, bioinformatics instruction is rarely integrated into life sciences curricula at the undergraduate level. To understand why, the Network for Integrating Bioinformatics into Life Sciences Education (NIBLSE, \"nibbles\") recently undertook an extensive survey of life sciences faculty in the United States. The survey responses to open-ended questions about barriers to integration were subjected to keyword analysis. The barrier most frequently reported by the ~1,260 respondents was lack of faculty training. Faculty at associates-granting institutions report the least training in bioinformatics and the least integration of bioinformatics into their teaching. Faculty from underrepresented minority groups (URMs) in STEM reported training barriers at a higher rate than others, although the number of URM respondents was small. Interestingly, the cohort of faculty with the most recently awarded PhD degrees reported the most training but were teaching bioinformatics at a lower rate than faculty who earned their degrees in previous decades. Other barriers reported included lack of student interest in bioinformatics; lack of student preparation in mathematics, statistics, and computer science; already overly full curricula; and limited access to resources, including hardware, software, and vetted teaching materials. The results of the survey, the largest to date on bioinformatics education, will guide efforts to further integrate bioinformatics instruction into undergraduate life sciences education.

scientific communication and education↗

bioRxiv2017

A Cross-Sectional Study Of Staphylococcus aureus Colonization And The Nasal And Oropharyngeal Microbiomes

BackgroundStaphylococcus aureus is a frequent cause of both infections globally. Colonization with the organism is known to increase the risk of developing infections and occurs in roughly one third of the general population. While many factors influence colonization, it has been demonstrated other members of the microbiome influence colonization with S. aureus. Here, we assessed the nasal and oropharyngeal microbiomes of healthy participants in relation to S. aureus colonization in a cross-sectional study using 16s rRNA sequencing of the v1-v3 region. As livestock workers have also been shown to be at an increased risk of carriage, we have also assessed microbiota differences in colonization status in a population of livestock workers.\n\nResultsIn both the nares and oropharynx, there were no microbiota differentially abundant between colonized and non-colonized persons. However, there was a significant difference in the beta diversity (Bray-Curtis distances) between carriers and non-carriers (P=0.002). When considering carriage stratified by livestock exposure, there were a number of differences. Most notably, colonized livestock workers had significantly more Porphyomonas (2-fold change = -8.54, P = 0.03) than the non-colonized livestock workers.\n\nConclusionsS. aureus is a frequent colonizer of the human upper respiratory tract, including the nares and oropharynx and causes a wide range of infections. Livestock workers are at increased risk for carriage. Interventions such as improving oral hygiene may lead to decreased S. aureus carriage by reducing other bacterial species such as Porphyomonas. Larger, longitudinal studies are needed to better explore what microorganisms may be associated with S. aureus colonization.

epidemiology↗

bioRxiv2017

Large scale variation in the rate of de novo mutation in humans and its relationship to divergence and diversity.

It has long been suspected that the rate of mutation varies across the human genome at a large scale based on the divergence between humans and other species. It is now possible to directly investigate this question using the large number of de novo mutations (DNMs) that have been discovered in humans through the sequencing of trios. We show that there is variation in the mutation rate at the 100KB, 1MB and 10MB scale that cannot be explained by variation at smaller scales, however the level of this variation is modest at large scales - at the 1MB scale we infer that ~90% of regions have a mutation rate within 50% of the mean. Different types of mutation show similar levels of variation and appear to vary in concert which suggests the pattern of mutation is relatively constant across the genome and hence unlikely to generate variation in GC-content. We confirm this using two different analyses. We find that genomic features explain less than 50% of the explainable variance in the rate of DNM. As expected the rate of divergence between species and the level of diversity within humans are correlated to the rate of DNM. However, the correlations are weaker than if all the variation in divergence was due to variation in the mutation rate. We provide evidence that this is due the effect of biased gene conversion on the probability that a mutation will become fixed. We find no evidence that linked selection affects the relationship between divergence and DNM density. In contrast to divergence, we find that most of the variation in diversity can be explained by variation in the mutation rate. Finally, we show that the correlation between divergence and DNM density declines as increasingly divergent species are considered.\n\nAuthor summaryUsing a dataset of 40,000 de novo mutations we show that there is large-scale variation in the mutation rate at the 100KB and 1MB scale. We show that different types of mutation vary in concert and in a manner that is not expected to generate variation in base composition; hence mutation bias is not responsible for the large-scale variation in base composition that is observed across human chromosomes. As expected large-scale variation in the rate of divergence between species and the variation within species across the genome, are correlated to the rate of mutation, but the correlation between divergence and the mutation rate is not as strong as they could be. We show that biased gene conversion is responsible for weakening the correlation. In contrast we find that most of the variation across the genome in diversity can be explained by variation in the mutation rate. Finally, we show that the correlation between the rate of mutation in humans and the divergence between humans and other species, weakens as the species become more divergent.

genomics↗

bioRxiv2016

Tuning the course of evolution on the biophysical fitness landscape of an RNA virus

Predicting viral evolution remains a major challenge with profound implications for public health. Viral evolutionary pathways are determined by the fitness landscape, which maps viral genotype to fitness. However, a quantitative description of the landscape and the evolutionary forces on it remain elusive. Here, we apply a biophysical fitness model based on capsid folding stability and antibody binding affinity to predict the evolutionary pathway of norovirus escaping a neutralizing antibody. The model is validated by experimental evolution in bulk culture and in a drop-based microfluidics device, the \"Evolution Chip\", which propagates millions of independent viral sub-populations. We demonstrate that along the axis of binding affinity, selection for escape variants and drift due to random mutations have the same direction. However, along folding stability, selection and drift are opposing forces whose balance is tuned by viral population size. Our results demonstrate that predictable epistatic tradeoffs shape viral evolution.

evolutionary biology↗