Gene Evolutionary Trajectories in M. tuberculosis Reveal Temporal Signs of Selection

Genetic differences between different Mycobacterium tuberculosis complex (MTBC) strains determine their ability to transmit within different host populations, their latency times, and their drug-resistance profiles. Said differences usually emerge through de novo mutations and are maintained or discarded by the balance of evolutionary forces. Using a dataset of ~5,000 strains representing global MTBC diversity, we determined the past and present selective forces that have shaped the current variability observed in the pathogen population. We identified regions that have evolved under changing types of selection since the time of the MTBC common ancestor. Our approach highlighted striking differences in the genome regions relevant for host-pathogen interaction and, in particular, suggested an adaptive role for the sensor protein of two-component systems. In addition, we applied our approach to successfully identify potential determinants of resistance to drugs administered as second-line tuberculosis treatments.

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Love the one you’re with: replicate viral adaptations converge on the same phenotypic change

PeerJ ◽

10.7717/peerj.2227 ◽

2016 ◽

Vol 4 ◽

pp. e2227 ◽

Cited By ~ 5

Author(s):

Craig R. Miller ◽

Anna C. Nagel ◽

LuAnn Scott ◽

Matt Settles ◽

Paul Joyce ◽

...

Keyword(s):

De Novo ◽

Regulatory Elements ◽

Host Cells ◽

Phenotypic Change ◽

De Novo Mutations ◽

Promoter Mutation ◽

Genetic Changes ◽

Evolutionary Forces ◽

Parallel Change ◽

The One

Parallelism is important because it reveals how inherently stochastic adaptation is. Even as we come to better understand evolutionary forces, stochasticity limits how well we can predict evolutionary outcomes. Here we sought to quantify parallelism and some of its underlying causes by adapting a bacteriophage (ID11) with nine different first-step mutations, each with eight-fold replication, for 100 passages. This was followed by whole-genome sequencing five isolates from each endpoint. A large amount of variation arose—281 mutational events occurred representing 112 unique mutations. At least 41% of the mutations and 77% of the events were adaptive. Within wells, populations generally experienced complex interference dynamics. The genome locations and counts of mutations were highly uneven: mutations were concentrated in two regulatory elements and three genes and, while 103 of the 112 (92%) of the mutations were observed in ≤4 wells, a few mutations arose many times. 91% of the wells and 81% of the isolates had a mutation in the D-promoter. Parallelism was moderate compared to previous experiments with this system. On average, wells shared 27% of their mutations at the DNA level and 38% when the definition of parallel change is expanded to include the same regulatory feature or residue. About half of the parallelism came from D-promoter mutations. Background had a small but significant effect on parallelism. Similarly, an analyses of epistasis between mutations and their ancestral background was significant, but the result was mostly driven by four individual mutations. A second analysis of epistasis focused on de novo mutations revealed that no isolate ever had more than one D-promoter mutation and that 56 of the 65 isolates lacking a D-promoter mutation had a mutation in genes D and/or E. We assayed time to lysis in four of these mutually exclusive mutations (the two most frequent D-promoter and two in gene D) across four genetic backgrounds. In all cases lysis was delayed. We postulate that because host cells were generally rare (i.e., high multiplicity of infection conditions developed), selection favored phage that delayed lysis to better exploit their current host (i.e., ‘love the one you’re with’). Thus, the vast majority of wells (at least 64 of 68, or 94%) arrived at the same phenotypic solution, but through a variety of genetic changes. We conclude that answering questions about the range of possible adaptive trajectories, parallelism, and the predictability of evolution requires attention to the many biological levels where the process of adaptation plays out.

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Trajectory and uniqueness of mutational signatures in yeast mutators

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2011332117 ◽

2020 ◽

Vol 117 (40) ◽

pp. 24947-24956 ◽

Cited By ~ 2

Author(s):

Sophie Loeillet ◽

Mareike Herzog ◽

Fabio Puddu ◽

Patricia Legoix ◽

Sylvain Baulande ◽

...

Keyword(s):

De Novo ◽

Clonal Evolution ◽

De Novo Mutations ◽

Mutational Signatures ◽

Base Substitutions ◽

Strong Stimulation ◽

Conserved Genes ◽

Genome Variations ◽

Selective Forces ◽

Brca1 Brca2

The acquisition of mutations plays critical roles in adaptation, evolution, senescence, and tumorigenesis. Massive genome sequencing has allowed extraction of specific features of many mutational landscapes but it remains difficult to retrospectively determine the mechanistic origin(s), selective forces, and trajectories of transient or persistent mutations and genome rearrangements. Here, we conducted a prospective reciprocal approach to inactivate 13 single or multiple evolutionary conserved genes involved in distinct genome maintenance processes and characterize de novo mutations in 274 diploid Saccharomyces cerevisiae mutation accumulation lines. This approach revealed the diversity, complexity, and ultimate uniqueness of mutational landscapes, differently composed of base substitutions, small insertions/deletions (InDels), structural variants, and/or ploidy variations. Several landscapes parallel the repertoire of mutational signatures in human cancers while others are either novel or composites of subsignatures resulting from distinct DNA damage lesions. Notably, the increase of base substitutions in the homologous recombination-deficient Rad51 mutant, specifically dependent on the Polζ translesion polymerase, yields COSMIC signature 3 observed in BRCA1/BRCA2-mutant breast cancer tumors. Furthermore, “mutome” analyses in highly polymorphic diploids and single-cell bottleneck lineages revealed a diverse spectrum of loss-of-heterozygosity (LOH) signatures characterized by interstitial and terminal chromosomal events resulting from interhomolog mitotic cross-overs. Following the appearance of heterozygous mutations, the strong stimulation of LOHs in the rad27/FEN1 and tsa1/PRDX1 backgrounds leads to fixation of homozygous mutations or their loss along the lineage. Overall, these mutomes and their trajectories provide a mechanistic framework to understand the origin and dynamics of genome variations that accumulate during clonal evolution.

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Genetic determinants of antibiotic resistance and the evolution of trade-offs during adaptation in a single patient

10.1101/2021.10.06.463321 ◽

2021 ◽

Author(s):

Robert J Woods ◽

Camilo Barbosa ◽

Laura Koepping ◽

Juan A. Raygoza Garay ◽

Michael Mwangi ◽

...

Keyword(s):

Antibiotic Resistance ◽

De Novo ◽

Laboratory Data ◽

Genetic Material ◽

Treatment Strategies ◽

Single Patient ◽

De Novo Mutations ◽

Collateral Sensitivity ◽

Trade Offs ◽

Evolutionary Trajectories

The processes by which pathogens evolve within single hosts dictate the efficacy of treatment strategies designed to slow antibiotic resistance evolution and influence the population-wide resistance levels. The aim of this study is to describe the underlying genetic and phenotypic changes leading to antibiotic resistance within a single patient who died as resistance evolved to available antibiotics. We assess whether robust patterns of collateral sensitivity and response to combinations exist that might have been leveraged to improve therapy. Whole-genome sequencing was completed for nine isolates taken from this patient over 279 days of chronic infection with Enterobacter hormaechei, along with systematic measurements of changes in resistance against five of the most relevant drugs considered for treatment. The entirety of the genetic change is consistent with de novo mutations and plasmid loss events, without the acquisition of foreign genetic material via horizontal gene transfer. The isolates formed three genetically distinct lineages, with early evolutionary trajectories being supplanted by previously unobserved multi-step evolutionary trajectories. Importantly, no single isolate evolved resistance to all of the antibiotics considered for treatment against E. hormaechei (i.e., none was pan-resistant). Patterns of collateral sensitivity and response to combination therapy revealed contrasting patterns across this diversifying population. Translating antibiotic resistance management strategies from theoretical and laboratory data to clinical situations, such as this, may require managing diverse populations with unpredictable resistance trajectories.

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Genome-Wide Identification of Genes Involved in Acid Stress Resistance of Salmonella Derby

Genes ◽

10.3390/genes12040476 ◽

2021 ◽

Vol 12 (4) ◽

pp. 476

Author(s):

Dan Gu ◽

Han Xue ◽

Xiaohui Yuan ◽

Jinyan Yu ◽

Xiaomeng Xu ◽

...

Keyword(s):

Wild Type Strain ◽

De Novo ◽

Acid Stress ◽

Acid Resistance ◽

Genome Wide ◽

Genes Expression ◽

Component Systems ◽

Two Component Systems ◽

Acidic Conditions ◽

Adhesion And Invasion

Resistance to and survival under acidic conditions are critical for Salmonella to infect the host. As one of the most prevalent serotypes identified in pigs and humans, how S. Derby overcomes acid stress remains unclear. Here, we de novo sequenced the genome of a representative S. Derby strain 14T from our S. Derby strain stock and identified its acid resistance-associated genes using Tn-seq analysis. A total of 35 genes, including those belonging to two-component systems (TCS) (cpxAR), the CRISPR-Cas system (casCE), and other systems, were identified as essential for 14T to survive under acid stress. The results demonstrated that the growth curve and survival ability of ΔcpxA and ΔcpxR were decreased under acid stress, and the adhesion and invasion abilities to the mouse colon cancer epithelial cells (MC38) of ΔcpxR were also decreased compared with the wild type strain, suggesting that the TCS CpxAR plays an essential role in the acid resistance and virulence of S. Derby. Also, CasC and CasE were found to be responsible for acid resistance in S. Derby. Our results indicate that acid stress induces multiple genes’ expression to mediate the acid resistance of S. Derby and enhance its pathogenesis during an infection.

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