Biology subjects

Abraham, P. E.

Publications and source records attributed to Abraham, P. E..

4 recordsLinked to original sources

bioRxiv2022

A guidance into the fungal metabolomic abyss: Network analysis for revealing relationships between exogenous compounds and their outputs

AO_SCPLOWBSTRACTC_SCPLOWFungal specialized metabolites include many bioactive compounds with potential applications as pharmaceuticals, agrochemical agents, and industrial chemicals. Exploring and discovering novel fungal metabolites is critical to combat antimicrobial resistance in various fields, including medicine and agriculture. Yet, identifying the conditions or treatments that will trigger the production of specialized metabolites in fungi can be cumbersome since most of these metabolites are not produced under standard culture conditions. Here, we introduce a data-driven algorithm comprising various network analysis routes to characterize the production of known and putative specialized metabolites and unknown analytes triggered by different exogenous compounds. We use bipartite networks to quantify the relationship between the metabolites and the treatments stimulating their production through two routes. The first, called the direct route, determines the production of known and putative specialized metabolites induced by a treatment. The second, called the auxiliary route, is specific for unknown analytes. We demonstrated the two routes by applying chitooligosaccharides and lipids at two different temperatures to the opportunistic human fungal pathogen Aspergillus fumigatus. We used various network centrality measures to rank the treatments based on their ability to trigger a broad range of specialized metabolites. The specialized metabolites were ranked based on their receptivity to various treatments. Altogether, our data-driven techniques can track the influence of any exogenous treatment or abiotic factor on the metabolomic output for targeted metabolite research. This approach can be applied to complement existing LC/MS analyses to overcome bottlenecks in drug discovery and development from fungi. NoticeThis manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). Author summaryTriggering silent biosynthetic gene clusters in fungi to produce specialized metabolites is a tedious process that requires assessing various environmental conditions, applications of epigenetic modulating agents, or co-cultures with other microbes. We provide a data-driven solution using network analysis, called "direct route", to characterize the production of known and putative specialized metabolites triggered by various exogenous compounds. We also provide a "auxiliary route" to distinguish unique unknown analytes amongst the abundantly produced analytes in response to these treatments. The developed techniques can assist researchers to identify treatments or applications that could positively influence the production of a targeted metabolite or recognize unique unknown analytes that can be further fractionated, characterized, and screened for their biological activities and hence, discover new metabolites.

systems biology↗

bioRxiv2021

An intein-mediated split-nCas9 system for base editing in plants

Virus-assisted delivery of the clustered regularly interspaced short palindromic (CRISPR)/CRISPR-associated (Cas) system represents a promising approach for editing plant genomes. However, the relatively large size of the CRISPR/Cas9 system is challenging to package into viral vectors with confined packaging capacity. To address this technical challenge, we developed a strategy that splits the required CRISPR-Cas9 components across a dual-vector system in which CRISPR-Cas reassembles into an active form following co-infection to achieve targeted genome editing in plant cells. An intein-mediated split system was adapted and optimized in plant cells by successfully demonstrating split-eYGFPuv expression. Using a plant-based biosensor, we demonstrated for the first time that the split-SpnCas9 is capable of inducing efficient base editing in plant cells and identified several valid split sites for future biodesign strategies. Overall, this strategy provides new opportunities to bridge different CRISPR/Cas9 tools including base editor, prime editor, and CRISPR activation with virus-mediated gene editing.

plant biology↗

bioRxiv2021

Plant-based biosensors for detecting CRISPR-mediated genome engineering

CRISPR/Cas has recently emerged as the most reliable system for genome engineering in various species. However, concerns about risks associated with CRISPR/Cas9 technology are increasing on potential unintended DNA changes that might accidentally arise from CRISPR gene editing. Developing a system that can detect and report the presence of active CRIPSR/Cas tools in biological systems is therefore very necessary. Here, we developed the real-time detection systems that can spontaneously indicate CRISPR-Cas tools for genome editing and gene regulation including CRISPR/Cas9 nuclease, base editing, prime editing and CRISPRa in plants. Using the fluorescence-based molecular biosensors, we demonstrated that the activities of CRISPR/Cas9 nuclease, base editing, prime editing and CRIPSRa can be effectively detected in transient expression via protoplast transformation and leaf infiltration (in Arabidopsis, poplar, and tobacco) and stable transformation in Arabidopsis.

plant biology↗

bioRxiv2021

Critical Assessment of Metaproteome Investigation (CAMPI): a Multi-Lab Comparison of Established Workflows

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carried out the first community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluated the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observed that variability at the peptide level was predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappeared at the protein group level. While differences were observed for predicted community composition, similar functional profiles were obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

microbiology↗