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Blaby, Ian

Publications and source records attributed to Blaby, Ian.

8 records
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DOE OSTI2024

Exploring the Structural, Biochemical, and Functional Diversity of Glycoside Hydrolase Family 12 from Penicillium subrubescens

Glycoside hydrolases (GHs) play an essential role in plant biomass degradation and modification for the sustainable production of biochemicals. The filamentous Ascomycete fungus Penicillium subrubescens contains a higher number of GH12 candidates compared to related species. Therefore, we aimed to compare P. subrubescens GH12s for their ability and substrate specificity for plant cell wall polysaccharide degradation and species’ potential as a source of novel enzymes for plant biomass valorization. Our re-evaluated phylogenetic analysis of fungal GH12 members showed that the P. subrubescens GH12s were located in different (new) clades. Biochemical characterization marked PsEglA as an endoglucanase and four other P. subrubescens GH12s (i.e., PsXegA–D) as xyloglucanases. Interestingly, structural features of PsXegD and PsXegE were more comparable to those of Basidiomycete GH12 xyloglucanases with a unique open substrate-binding cleft. PsUegA displayed dual xyloglucanase and endoglucanase activity and also showed distinct structural features. Comparative transcriptome analysis supported the functional diversity of P. subrubescens GH12s in plant biomass degradation. The gene encoding PsUegA was expressed under diverse conditions, suggesting a scouting role for this enzyme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

An efficient cre‐based workflow for genomic integration and expression of large biosynthetic pathways in Eubacterium limosum

Abstract Acetogenic Clostridia are obligate anaerobes that have emerged as promising microbes for the renewable production of biochemicals owing to their ability to efficiently metabolize sustainable single‐carbon feedstocks. Additionally, Clostridia are increasingly recognized for their biosynthetic potential, with recent discoveries of diverse secondary metabolites ranging from antibiotics to pigments to modulators of the human gut microbiota. Lack of efficient methods for genomic integration and expression of large heterologous DNA constructs remains a major challenge in studying biosynthesis in Clostridia and using them for metabolic engineering applications. To overcome this problem, we harnessed chassis‐independent recombinase‐assisted genome engineering (CRAGE) to develop a workflow for facile integration of large gene clusters (>10 kb) into the human gut acetogen Eubacterium limosum . We then integrated a non‐ribosomal peptide synthetase gene cluster from the gut anaerobe Clostridium leptum , which previously produced no detectable product in traditional heterologous hosts. Chromosomal expression in E. limosum without further optimization led to production of phevalin at 2.4 mg/L. These results further expand the molecular toolkit for a highly tractable member of the Clostridia, paving the way for sophisticated pathway engineering efforts, and highlighting the potential of E. limosum as a Clostridial chassis for exploration of anaerobic natural product biosynthesis.

Sanford, Patrick A.↗
DOE OSTI2023

gRNA-SeqRET: a universal tool for targeted and genome-scale gRNA design and sequence extraction for prokaryotes and eukaryotes

High-throughput genetic screening is frequently employed to rapidly associate gene with phenotype and establish sequence-function relationships. With the advent of CRISPR technology, and the ability to functionally interrogate previously genetically recalcitrant organisms, non-model organisms can be investigated using pooled guide RNA (gRNA) libraries and sequencing-based assays to quantitatively assess fitness of every targeted locus in parallel. To aid the construction of pooled gRNA assemblies, we have developed an in silico design workflow for gRNA selection using the gRNA Sequence Region Extraction Tool (gRNA-SeqRET). Built upon the previously developed CCTop, gRNA-SeqRET enables automated, scalable design of gRNA libraries that target user-specified regions or whole genomes of any prokaryote or eukaryote. Additionally, gRNA-SeqRET automates the bulk extraction of any regions of sequence relative to genes or other features, aiding in the design of homology arms for insertion or deletion constructs. We also assess in silico the application of a designed gRNA library to other closely related genomes and demonstrate that for very closely related organisms Average Nucleotide Identity (ANI) > 95% a large fraction of the library may be of relevance. The gRNA-SeqRET web application pipeline can be accessed at https://grna.jgi.doe.gov. The source code is comprised of freely available software tools and customized Python scripts, and is available at https://bitbucket.org/berkeleylab/grnadesigner/src/master/ under a modified BSD open-source license (https://bitbucket.org/berkeleylab/grnadesigner).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Sensitivity Analysis of Genome-Scale Metabolic Flux Prediction

TRIMER, Transcription Regulation Integrated with MEtabolic Regulation, is a genome-scale modeling pipeline targeting at metabolic engineering applications. Using TRIMER, regulated metabolic reactions can be effectively predicted by integrative modeling of metabolic reactions with a Transcription Factor (TF)-gene regulatory network (TRN), which is modeled via a Bayesian network (BN). In this paper, we focus on sensitivity analysis of metabolic flux prediction for uncertainty quantification of BN structures for TRN modeling in TRIMER. We propose a computational strategy to construct the uncertainty class of TRN models based on the inferred regulatory order uncertainty given transcriptomic expression data. With that, we analyze the prediction sensitivity of the TRIMER pipeline for the metabolite yields of interest. The obtained sensitivity analyses can guide Optimal Experimental Design (OED) to help acquire new data that can enhance TRN modeling and achieve specific metabolic engineering objectives, including metabolite yield alterations. Here we have performed small- and large-scale simulated experiments, demonstrating the effectiveness of our developed sensitivity analysis strategy for BN structure learning to quantify the edge importance in terms of metabolic flux prediction uncertainty reduction and its potential to effectively guide OED.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A roadmap for the functional annotation of protein families: a community perspective

Over the last 25 years, biology has entered the genomic era and is becoming a science of ‘big data’. Most interpretations of genomic analyses rely on accurate functional annotations of the proteins encoded by more than 500 000 genomes sequenced to date. By different estimates, only half the predicted sequenced proteins carry an accurate functional annotation, and this percentage varies drastically between different organismal lineages. Such a large gap in knowledge hampers all aspects of biological enterprise and, thereby, is standing in the way of genomic biology reaching its full potential. A brainstorming meeting to address this issue funded by the National Science Foundation was held during 3–4 February 2022. Bringing together data scientists, biocurators, computational biologists and experimentalists within the same venue allowed for a comprehensive assessment of the current state of functional annotations of protein families. Further, major issues that were obstructing the field were identified and discussed, which ultimately allowed for the proposal of solutions on how to move forward.

59 BASIC BIOLOGICAL SCIENCES↗