Wickerhamiella bidentis sp. nov., a novel yeast species isolated from flowers and insects in Japan.

Two strains were isolated from flowers and insects in Japan, namely NBRC 115686T and NBRC 115687, respectively. Based on sequence analysis of the D1/D2 domain of the 26S large subunit (LSU) rRNA gene and the internal transcribed spacer (ITS) region and physiological characteristics, these strains were found to represent a novel yeast species of the genus Wickerhamiella. Considering pairwise sequence similarity, NBRC 115686T and NBRC 115687 differ from the type strain of the most closely related species, Wickerhamiella galacta NRRL Y-17645T, by 65-66 nucleotide substitutions with 12 gaps (11.65-11.83 %) in the D1/D2 domain of the LSU rRNA gene. The novel species differ from the closely related Wickerhamiella species in some physiological characteristics. For example, compared with Wickerhamiella galacta JCM 8257T, NBRC 115686T and NBRC 115687 assimilated d-galactose, and could grow at 35 and 37 °C. Hence, the name Wickerhamiella bidentis sp. nov. is proposed to accommodate this species in the genus Wickerhamiella. The holotype is NBRC 115686T (ex-type strain JCM 35540=CBS 18008).

Purifying selection enduringly acts on the sequence evolution of highly expressed proteins in Escherichia coli.

The evolutionary speed of a protein sequence is constrained by its expression level, with highly expressed proteins evolving relatively slowly. This negative correlation between expression levels and evolutionary rates (known as the E-R anticorrelation) has already been widely observed in past macroevolution between species from bacteria to animals. However, it remains unclear whether this seemingly general law also governs recent evolution, including past and de novo, within a species. However, the advent of genomic sequencing and high-throughput phenotyping, particularly for bacteria, has revealed fundamental gaps between the 2 evolutionary processes and has provided empirical data opposing the possible underlying mechanisms which are widely believed. These conflicts raise questions about the generalization of the E-R anticorrelation and the relevance of plausible mechanisms. To explore the ubiquitous impact of expression levels on molecular evolution and test the relevance of the possible underlying mechanisms, we analyzed the genome sequences of 99 strains of Escherichia coli for evolution within species in nature. We also analyzed genomic mutations accumulated under laboratory conditions as a model of de novo evolution within species. Here, we show that E-R anticorrelation is significant in both past and de novo evolution within species in E. coli. Our data also confirmed ongoing purifying selection on highly expressed genes. Ongoing selection included codon-level purifying selection, supporting the relevance of the underlying mechanisms. However, the impact of codon-level purifying selection on the constraints in evolution within species might be smaller than previously expected from evolution between species.

The sixth transmembrane region of a pheromone G-protein coupled receptor, Map3, is implicated in discrimination of closely related pheromones in Schizosaccharomyces pombe.

Most sexually reproducing organisms have the ability to recognize individuals of the same species. In ascomycete fungi including yeasts, mating between cells of opposite mating type depends on the molecular recognition of two peptidyl mating pheromones by their corresponding G-protein coupled receptors (GPCRs). Although such pheromone/receptor systems are likely to function in both mate choice and prezygotic isolation, very few studies have focused on the stringency of pheromone receptors. The fission yeast Schizosaccharomyces pombe has two mating types, Plus (P) and Minus (M). Here, we investigated the stringency of the two GPCRs, Mam2 and Map3, for their respective pheromones, P-factor and M-factor, in fission yeast. First, we switched GPCRs between S. pombe and the closely related species Schizosaccharomyces octosporus, which showed that SoMam2 (Mam2 of S. octosporus) is partially functional in S. pombe, whereas SoMap3 (Map3 of S. octosporus) is not interchangeable. Next, we swapped individual domains of Mam2 and Map3 with the respective domains in SoMam2 and SoMap3, which revealed differences between the receptors both in the intracellular regions that regulate the downstream signaling of pheromones and in the activation by the pheromone. In particular, we demonstrated that two amino acid residues of Map3, F214 and F215, are key residues important for discrimination of closely related M-factors. Thus, the differences in these two GPCRs might reflect the significantly distinct stringency/flexibility of their respective pheromone/receptor systems; nevertheless, species-specific pheromone recognition remains incomplete.

Laboratory evolution of Mycobacterium on agar plates for analysis of resistance acquisition and drug sensitivity profiles.

Drug-resistant tuberculosis (TB) is a growing public health problem. There is an urgent need for information regarding cross-resistance and collateral sensitivity relationships among drugs and the genetic determinants of anti-TB drug resistance for developing strategies to suppress the emergence of drug-resistant pathogens. To identify mutations that confer resistance to anti-TB drugs in Mycobacterium species, we performed the laboratory evolution of nonpathogenic Mycobacterium smegmatis, which is closely related to Mycobacterium tuberculosis, against ten anti-TB drugs. Next, we performed whole-genome sequencing and quantified the resistance profiles of each drug-resistant strain against 24 drugs. We identified the genes with novel meropenem (MP) and linezolid (LZD) resistance-conferring mutation, which also have orthologs, in M. tuberculosis H37Rv. Among the 240 possible drug combinations, we identified 24 pairs that confer cross-resistance and 18 pairs that confer collateral sensitivity. The acquisition of bedaquiline or linezolid resistance resulted in collateral sensitivity to several drugs, while the acquisition of MP resistance led to multidrug resistance. The MP-evolved strains showed cross-resistance to rifampicin and clarithromycin owing to the acquisition of a mutation in the intergenic region of the Rv2864c ortholog, which encodes a penicillin-binding protein, at an early stage. These results provide a new insight to tackle drug-resistant TB.

Elevated Sporulation Efficiency in Fission Yeast Schizosaccharomyces japonicus Strains Isolated from Drosophila.

The fission yeast Schizosaccharomyces japonicus, comprising S. japonicus var. japonicus and S. japonicus var. versatilis varieties, has unique characteristics such as striking hyphal growth not seen in other Schizosaccharomyces species; however, information on its diversity and evolution, in particular mating and sporulation, remains limited. Here we compared the growth and mating phenotypes of 17 wild strains of S. japonicus, including eight S. japonicus var. japonicus strains newly isolated from an insect (Drosophila). Unlike existing wild strains isolated from fruits/plants, the strains isolated from Drosophila sporulated at high frequency even under nitrogen-abundant conditions. In addition, one of the strains from Drosophila was stained by iodine vapor, although the type strain of S. japonicus var. japonicus is not stained. Sequence analysis further showed that the nucleotide and amino acid sequences of pheromone-related genes have diversified among the eight strains from Drosophila, suggesting crossing between S. japonicus cells of different genetic backgrounds occurs frequently in this insect. Much of yeast ecology remains unclear, but our findings suggest that insects such as Drosophila might be a good niche for mating and sporulation, and will provide a basis for the understanding of sporulation mechanisms via signal transduction, as well as the ecology and evolution of yeast.

High-throughput laboratory evolution reveals evolutionary constraints in Escherichia coli.

Understanding the constraints that shape the evolution of antibiotic resistance is critical for predicting and controlling drug resistance. Despite its importance, however, a systematic investigation of evolutionary constraints is lacking. Here, we perform a high-throughput laboratory evolution of Escherichia coli under the addition of 95 antibacterial chemicals and quantified the transcriptome, resistance, and genomic profiles for the evolved strains. Utilizing machine learning techniques, we analyze the phenotype-genotype data and identified low dimensional phenotypic states among the evolved strains. Further analysis reveals the underlying biological processes responsible for these distinct states, leading to the identification of trade-off relationships associated with drug resistance. We also report a decelerated evolution of ß-lactam resistance, a phenomenon experienced by certain strains under various stresses resulting in higher acquired resistance to ß-lactams compared to strains directly selected by ß-lactams. These findings bridge the genotypic, gene expression, and drug resistance gap, while contributing to a better understanding of evolutionary constraints for antibiotic resistance.

Complete Genome Sequences of Three Star-Shaped Bacteria, Stella humosa, Stella vacuolata, and Stella Species ATCC 35155.

Stella species are unique star-shaped alphaproteobacteria found in various environments. We report the complete genome sequences of three Stella strains, Stella humosa ATCC 43930, Stella vacuolata ATCC 43931, and Stella species ATCC 35155. These are the first complete genome sequences of members of the genus Stella.

High-throughput identification of the sensitivities of an Escherichia coli ΔrecA mutant strain to various chemical compounds.

Antibiotic resistance is considered a global threat to public health. Adaptive resistance mutations and the acquisition of resistance genes by horizontal gene transfer are known to be facilitated by the RecA-dependent SOS response during antibiotic treatment, making RecA inhibitors promising agents for the prevention of antibiotic resistance. However, the impact of RecA inactivation on antibiotic sensitivities remains unclear. Therefore, in this study, we performed high-throughput screening to determine the minimum inhibitory concentrations (MICs) of 217 chemicals, including both antibiotics and toxic chemicals of unknown drug action, in the wild-type MDS42 and the ΔrecA mutant strains of Escherichia coli. The ΔrecA mutant showed increased sensitivity to DNA-damaging agents, DNA replication inhibitors, and chromate stress, as well as to other chemicals, such as S-(2-aminoethyl)-L-cysteine, L-histidine, ruthenium red, D-penicillamine, carbonyl cyanide 3-chlorophenylhydrazone (CCCP), cerulenin, and L-cysteine. Microarray analysis showed further that the ΔrecA mutant had lower expressions of glnK, nac, and glnLG, which encode nitrogen assimilation regulators, as well as amtB, which encodes an ammonium transporter, compared with the wild type. These findings suggest that the ΔrecA mutation affects not only the SOS response but also amino acid metabolism.

Prediction of Cross-resistance and Collateral Sensitivity by Gene Expression profiles and Genomic Mutations.

In adaptive evolution, an increase in fitness to an environment is frequently accompanied by changes in fitness to other environmental conditions, called cross-resistance and sensitivity. Although the networks between fitness changes affect the course of evolution substantially, the mechanisms underlying such fitness changes are yet to be fully elucidated. Herein, we performed high-throughput laboratory evolution of Escherichia coli under various stress conditions using an automated culture system, and quantified how the acquisition of resistance to one stressor alters the resistance to other stressors. We demonstrated that resistance changes could be quantitatively predicted based on changes in the transcriptome of the resistant strains. We also identified several genes and gene functions, for which mutations were commonly fixed in the strains resistant to the same stress, which could partially explain the observed cross-resistance and collateral sensitivity. The integration of transcriptome and genome data enabled us to clarify the bacterial stress resistance mechanisms.