Mutation rate variability as a driving force in adaptive evolution

Evolution of antimicrobial resistance in E. coli biofilm treated with high doses of ciprofloxacin

The evolution of antimicrobial resistance (AMR) has mainly been studied in planktonic bacteria exposed to sub-inhibitory antimicrobial (AM) concentrations. However, in a number of infections that are treated with AMs the bacteria are located in biofilms where they tolerate high doses of AM. In the present study, we continuously exposed biofilm residing E. coli at body temperature to high ciprofloxacin (CIP) concentrations increasing from 4 to 130 times the minimal inhibitory concentration (MIC), i.e., from 0.06 to 2.0 mg/L. After 1 week, the biofilms were full of CIP resistant bacteria. The evolutionary trajectory observed was the same as described in the literature for planktonic bacteria, i.e., starting with a single mutation in the target gene gyrA followed by mutations in parC, gyrB, and parE, as well as in genes for regulation of multidrug efflux pump systems and outer membrane porins. Strains with higher numbers of these mutations also displayed higher MIC values. Furthermore, the evolution of CIP resistance was more rapid, and resulted in strains with higher MIC values, when the bacteria were biofilm residing than when they were in a planktonic suspension. These results may indicate that extensive clinical AM treatment of biofilm-residing bacteria may not only fail to eradicate the infection but also pose an increased risk of AMR development.

DRAGON: Harnessing the power of DNA repair for accelerating genome evolution in Corynebacterium glutamicum

Hypermutation is a robust phenotype characterized by high elevation of spontaneous mutation rates, which has been shown to facilitate rapid adaptation to the stressful environments by hitchhiking with favorable mutations. Accumulating evidence argues that deficient DNA repair can give rise to hypermutation events in bacteria. Here, we provided a comprehensive survey of DNA repair systems to identify promising targets ensuring high DNA fidelity in Corynebacterium glutamicum. Four effective DNA repair factors, including nucS, tag, xpb, and dinP, were found to be strongly associated with the occurrence of hypermutable phenotypes, and these targets were then engineered to establish a CRISPRi-based all-in-one plasmid system for genome mutagenesis. On the basis of these findings, we presented a novel evolutionary engineering method named "DNA repair-assisted genome evolution (DRAGON)". As a proof-of-concept, DRAGON strategy was successfully applied to facilitate rapid acquisition of microbial robustness in C. glutamicum, such as increased tolerances towards kanamycin, acidic pH and high L-serine, showing its promise and potential for rapid strain improvement. Overall, our study will offer new insights into the understanding of DNA repair and evolutionary adaptation in C. glutamicum.

Protein Engineering in the Design of Protein-Protein Interactions: SARS-CoV-2 Inhibitors as a Test Case

The formation of specific protein-protein interactions (PPIs) drive most biological processes. Malfunction of such interactions is the molecular driver of many diseases. Our ability to engineer existing PPIs or create new ones has become a vital research tool. In addition, engineered proteins with new or altered interactions are among the most critical drugs that have been developed in recent years. These include antibodies, cytokines, inhibitors, and others. Here, we provide a perspective on the current status of the methods used to engineer new or altered PPIs. The emergence of the COVID-19 pandemic, which resulted in a worldwide quest to develop specific PPI inhibitors as drugs, provided an up-to-date and state-of-the-art status report on the methodologies for engineering PPIs targeting the interaction of the viral spike protein with its cellular target, ACE2. Multiple, very high affinity binders were generated within a few months using in vitro evolution by itself, or in combination with computational design. The different experimental and computational methods used to block this interaction provide a road map for the future of PPI engineering.

Leaf Bleaching in Rice: A New Disease in Vietnam Caused by Methylobacterium indicum, Its Genomic Characterization and the Development of a Suitable Detection Technique

A new disease in rice that is characterized by leaf bleaching was recently identified in some fields in the Mekong Delta region of Vietnam. The present study was the first to isolate and identify the pathogen of this disease. We confirmed that leaf bleaching symptoms were due to infection with Methylobacterium indicum bacteria using molecular biology approaches. A full-length genome analysis of pathogenic Methylobacterium strain VL1 revealed that it comprises a single chromosome and six plasmids, with a total size of 7.05‍ ‍Mbp and GC content of 70.5%. The genomic features of VL1 were similar to those of the non-pathogenic M. indicum strain SE2.11^T; however, VL1 possessed additional unique genes, including those related to homoserine lactone biosynthesis. We established a loop-mediated isothermal amplification (LAMP) assay using the unique sequences of VL1 as target sequences for the rapid and simple detection of pathogenic M. indicum strains. Our initial evaluation demonstrated that the LAMP assay successfully distinguished between pathogenic and non-pathogenic strains infecting rice plants in a rapid and sensitive manner. The present results provide insights into the pathogenesis and development of control measures for novel rice diseases.

Genomic Changes and Genetic Divergence of Vibrio alginolyticus Under Phage Infection Stress Revealed by Whole-Genome Sequencing and Resequencing

Bacteriophages (phages) and their bacterial hosts were the most abundant and genetically highly diverse organisms on the earth. In this study, a series of phage-resistant mutant (PRM) strains derived from Vibrio alginolyticus were isolated and Infrequent-restriction-site PCR (IRS-PCR) was used to investigate the genetic diversity of the PRM strains. Phenotypic variations of eight PRM strains were analyzed using profiles of utilizing carbon sources and chemical sensitivity. Genetic variations of eight PRM strains and coevolved V. alginolyticus populations with phages were analyzed by whole-genome sequencing and resequencing, respectively. The results indicated that eight genetically discrepant PRM stains exhibited abundant and abundant phenotypic variations. Eight PRM strains and coevolved V. alginolyticus populations (VE1, VE2, and VE3) contained numerous single nucleotide variations (SNVs) and insertions/indels (InDels) and exhibited obvious genetic divergence. Most of the SNVs and InDels in coding genes were related to the synthesis of flagellar, extracellular polysaccharide (EPS), which often served as the receptors of phage invasion. The PRM strains and the coevolved cell populations also contained frequent mutations in tRNA and rRNA genes. Two out of three coevolved populations (VE1 and VE2) contained a large mutation segment severely deconstructing gene nrdA, which was predictably responsible for the booming of mutation rate in the genome. In summary, numerous mutations and genetic divergence were detected in the genomes of V. alginolyticus PRM strains and in coevolved cell populations of V. alginolyticus under phage infection stress. The phage infection stress may provide an important force driving genomic evolution of V. alginolyticus.

Morphological Characters Can Strongly Influence Early Animal Relationships Inferred from Phylogenomic Data Sets

There are considerable phylogenetic incongruencies between morphological and phylogenomic data for the deep evolution of animals. This has contributed to a heated debate over the earliest-branching lineage of the animal kingdom: the sister to all other Metazoa (SOM). Here, we use published phylogenomic data sets ($\sim $45,000-400,000 characters in size with $\sim $15-100 taxa) that focus on early metazoan phylogeny to evaluate the impact of incorporating morphological data sets ($\sim $15-275 characters). We additionally use small exemplar data sets to quantify how increased taxon sampling can help stabilize phylogenetic inferences. We apply a plethora of common methods, that is, likelihood models and their "equivalent" under parsimony: character weighting schemes. Our results are at odds with the typical view of phylogenomics, that is, that genomic-scale data sets will swamp out inferences from morphological data. Instead, weighting morphological data 2-10$\times $ in both likelihood and parsimony can in some cases "flip" which phylum is inferred to be the SOM. This typically results in the molecular hypothesis of Ctenophora as the SOM flipping to Porifera (or occasionally Placozoa). However, greater taxon sampling improves phylogenetic stability, with some of the larger molecular data sets ($>$200,000 characters and up to $\sim $100 taxa) showing node stability even with $\geqq100\times $ upweighting of morphological data. Accordingly, our analyses have three strong messages. 1) The assumption that genomic data will automatically "swamp out" morphological data is not always true for the SOM question. Morphological data have a strong influence in our analyses of combined data sets, even when outnumbered thousands of times by molecular data. Morphology therefore should not be counted out a priori. 2) We here quantify for the first time how the stability of the SOM node improves for several genomic data sets when the taxon sampling is increased. 3) The patterns of "flipping points" (i.e., the weighting of morphological data it takes to change the inferred SOM) carry information about the phylogenetic stability of matrices. The weighting space is an innovative way to assess comparability of data sets that could be developed into a new sensitivity analysis tool. [Metazoa; Morphology; Phylogenomics; Weighting.].