Understanding metabolic adaptation by using bacterial laboratory evolution and trans-omics analysis

Comparative Genomic and Transcriptomic Analysis of Phenol Degradation and Tolerance in Acinetobacter lwoffii through Adaptive Evolution

Microorganism-based methods have been widely applied for the treatment of phenol-polluted environments. The previously isolated Acinetobacter lwoffii NL1 strain could completely degrade 0.5 g/L phenol within 12 h, but not higher concentrations of phenol. In this study, we developed an evolutionary strain NL115, through adaptive laboratory evolution, which possessed improved degradation ability and was able to degrade 1.5 g/L phenol within 12 h. Compared with that of the starting strain NL1, the concentration of degradable phenol by the developed strain increased three-fold; its phenol tolerance was also enhanced. Furthermore, comparative genomics showed that sense mutations mainly occurred in genes encoding alkyl hydroperoxide reductase, phenol hydroxylase, 30S ribosomal protein, and mercury resistance operon. Comparative transcriptomics between A. lwoffii NL115 and NL1 revealed the enrichment of direct degradation, stress resistance, and vital activity processes among the metabolic responses of A. lwoffii adapted to phenol stress. Among these, all the upregulated genes (log2fold-change > 5) encoded peroxidases. A phenotypic comparison of A. lwoffii NL1 and NL115 found that the adapted strain NL115 exhibited strengthened antioxidant capacity. Furthermore, the increased enzymatic activities of phenol hydroxylase and alkyl hydroperoxide reductase in A. lwoffii NL115 validated their response to phenol. Overall, this study provides insight into the mechanism of efficient phenol degradation through adaptive microbial evolution and can help to drive improvements in phenol bioremediation.

Contributions of Adaptive Laboratory Evolution towards the Enhancement of the Biotechnological Potential of Non-Conventional Yeast Species

Changes in biological properties over several generations, induced by controlling short-term evolutionary processes in the laboratory through selective pressure, and whole-genome re-sequencing, help determine the genetic basis of microorganism's adaptive laboratory evolution (ALE). Due to the versatility of this technique and the imminent urgency for alternatives to petroleum-based strategies, ALE has been actively conducted for several yeasts, primarily using the conventional species Saccharomyces cerevisiae, but also non-conventional yeasts. As a hot topic at the moment since genetically modified organisms are a debatable subject and a global consensus on their employment has not yet been attained, a panoply of new studies employing ALE approaches have emerged and many different applications have been exploited in this context. In the present review, we gathered, for the first time, relevant studies showing the ALE of non-conventional yeast species towards their biotechnological improvement, cataloging them according to the aim of the study, and comparing them considering the species used, the outcome of the experiment, and the employed methodology. This review sheds light on the applicability of ALE as a powerful tool to enhance species features and improve their performance in biotechnology, with emphasis on the non-conventional yeast species, as an alternative or in combination with genome editing approaches.

Quantitative metabolic fluxes regulated by trans-omic networks

Cells change their metabolism in response to internal and external conditions by regulating the trans-omic network, which is a global biochemical network with multiple omic layers. Metabolic flux is a direct measure of the activity of a metabolic reaction that provides valuable information for understanding complex trans-omic networks. Over the past decades, techniques to determine metabolic fluxes, including 13C-metabolic flux analysis (13C-MFA), flux balance analysis (FBA), and kinetic modeling, have been developed. Recent studies that acquire quantitative metabolic flux and multi-omic data have greatly advanced the quantitative understanding and prediction of metabolism-centric trans-omic networks. In this review, we present an overview of 13C-MFA, FBA, and kinetic modeling as the main techniques to determine quantitative metabolic fluxes, and discuss their advantages and disadvantages. We also introduce case studies with the aim of understanding complex metabolism-centric trans-omic networks based on the determination of metabolic fluxes.

Microbial adaptive evolution

Bacterial species can adapt to significant changes in their environment by mutation followed by selection, a phenomenon known as “adaptive evolution.” With the development of bioinformatics and genetic engineering, research on adaptive evolution has progressed rapidly, as have applications of the process. In this review, we summarize various mechanisms of bacterial adaptive evolution, the technologies used for studying it, and successful applications of the method in research and industry. We particularly highlight the contributions of Dr. L. O. Ingram. Microbial adaptive evolution has significant impact on our society not only from its industrial applications, but also in the evolution, emergence, and control of various pathogens.

Integrated mass spectrometry-based multi-omics for elucidating mechanisms of bacterial virulence

Despite being considered the simplest form of life, bacteria remain enigmatic, particularly in light of pathogenesis and evolving antimicrobial resistance. After three decades of genomics, we remain some way from understanding these organisms, and a substantial proportion of genes remain functionally unknown. Methodological advances, principally mass spectrometry (MS), are paving the way for parallel analysis of the proteome, metabolome and lipidome. Each provides a global, complementary assay, in addition to genomics, and the ability to better comprehend how pathogens respond to changes in their internal (e.g. mutation) and external environments consistent with infection-like conditions. Such responses include accessing necessary nutrients for survival in a hostile environment where co-colonizing bacteria and normal flora are acclimated to the prevailing conditions. Multi-omics can be harnessed across temporal and spatial (sub-cellular) dimensions to understand adaptation at the molecular level. Gene deletion libraries, in conjunction with large-scale approaches and evolving bioinformatics integration, will greatly facilitate next-generation vaccines and antimicrobial interventions by highlighting novel targets and pathogen-specific pathways. MS is also central in phenotypic characterization of surface biomolecules such as lipid A, as well as aiding in the determination of protein interactions and complexes. There is increasing evidence that bacteria are capable of widespread post-translational modification, including phosphorylation, glycosylation and acetylation; with each contributing to virulence. This review focuses on the bacterial genotype to phenotype transition and surveys the recent literature showing how the genome can be validated at the proteome, metabolome and lipidome levels to provide an integrated view of organism response to host conditions.

Biophysical Reviews: 2020-looking back, going forward

After first describing the issue contents (Biophysical Reviews-Volume 12 Issue 6), this Editorial goes on to provide a short round-up of the activities of the journal in 2020. Directly following this Editorial are two obituaries marking the recent deaths of Prof. Fumio Oosawa (Japan) and Dr. Herbert Tabor (USA)-two major figures in Biophysical/Biochemical science from the last 100 years.

Biophysical Reviews-Quantitative analysis of biological phenomenon

This Editorial first describes the articles constituting the current Issue (Volume 12 Issue 3). It then goes on to outline the formal invitation procedure for those interested in submitting a review article to the journal. The Editorial concludes by describing the nomination process for the 2021 Michèle Auger Award for Young Scientists' Independent Research.