Biology subjects

Coelho, N. C.

Publications and source records attributed to Coelho, N. C..

3 recordsLinked to original sources

bioRxiv2026

Environmental stress and phenotypic tradeoff modulate the adaptive potential of novel coding sequences for de novo gene birth

Novel protein-coding genes can emerge de novo from ancestrally noncoding sequences and promote adaptation to environmental stresses. Previous work proposes that pervasive translation of lowly expressed open reading frames (ORFs) in noncoding regions creates a rich reservoir of 'proto-genes,' of which subsequent acquisition of gene-like properties, such as increased expression, may be favored or purged by natural selection depending on their phenotypic impact. However, whether and how environmental conditions affect the phenotypic impact of proto-genes remains unclear. Here, we experimentally simulated proto-gene evolution in Saccharomyces cerevisiae by individually increasing the expression of nearly a thousand de novo ORFs with prior evidence of native translation under osmotic and endoplasmic-reticulum stress and in control environments. High-throughput phenotyping revealed that growth effects of increased expression varied strongly across environments for de novo ORFs. A follow-up screen across 22 diverse environments revealed a robust positive correlation between environmental stress severity and the mean growth effects of increased de novo ORF expression. At the individual level, 5.4% of tested de novo ORFs conferred beneficial phenotypes in at least one environment, and 83.3% of these also caused deleterious effects elsewhere, revealing widespread phenotypic tradeoffs. We demonstrate that increased expression of the de novo translated ORF YLR112W results in increased growth in the presence of rapamycin through general dampening of the growth-repressing transcriptomic response induced by this drug. Together, these findings demonstrate that stress severity shapes the phenotypic consequences of increased proto-gene expression and shed light on tradeoffs and transcriptome remodeling as mechanisms underlying such environmental dependency.

evolutionary biology↗

bioRxiv2022

Unexpected growth of a classic yeast auxotroph

Organisms must either synthesize or assimilate essential organic compounds to survive. The homocysteine synthase Met15 has been considered essential for inorganic sulfur assimilation in yeast since its discovery in the 1970s. As a result, MET15 has served as a genetic marker for hundreds of experiments that play a foundational role in eukaryote genetics and systems biology. Nevertheless, we demonstrate here through structural and evolutionary modeling, in vitro kinetic assays, and genetic complementation, that an alternative homocysteine synthase encoded by the previously uncharacterized gene YLL058W enables cells lacking Met15 to assimilate enough inorganic sulfur for survival and proliferation. These cells however fail to grow in patches or liquid cultures unless provided with exogenous methionine or other organosulfurs. We show that this growth failure, which has historically justified the status of MET15 as a classic auxotrophic marker, is largely explained by toxic accumulation of the gas hydrogen sulfide due to a metabolic bottleneck. When patched or cultured with a hydrogen sulfide chelator, and when propagated as colony grids, cells without Met15 assimilate inorganic sulfur and grow, and cells with Met15 achieve even higher yields. Thus, Met15 is not essential for inorganic sulfur assimilation in yeast. Instead, MET15 is the first example of a yeast gene whose loss conditionally prevents growth in a manner that depends on local gas exchange. Our results have broad implications for investigations of sulfur metabolism, including studies of stress response, methionine restriction, and aging. More generally, our findings illustrate how unappreciated experimental variables can obfuscate biological discovery.

molecular biology↗

bioRxiv2020

LI Detector: a framework for sensitive colony-based screens regardless of the distribution of fitness effects

Microbial growth characteristics have long been used to investigate fundamental questions of biology. Colony-based high-throughput screens enable parallel fitness estimation of thousands of individual strains using colony growth as a proxy for fitness. However, fitness estimation is complicated by spatial biases affecting colony growth, including uneven nutrient distribution, agar surface irregularities, and batch effects. Analytical methods that have been developed to correct for these spatial biases rely on the following assumptions: i) that fitness effects are normally distributed, and ii) that most genetic perturbations lead to minor changes in fitness. Although reasonable for many applications, these assumptions are not always warranted and can limit the ability to detect small fitness effects. Beneficial fitness effects, in particular, are notoriously difficult to detect under these assumptions. Here, we developed the linear interpolation-based detector (LI Detector) framework to enable sensitive colony-based screening without making prior assumptions about the underlying distribution of fitness effects. The LI Detector uses a grid of reference colonies to assign a relative fitness value to every colony on the plate. We show that the LI Detector is effective in correcting for spatial biases and equally sensitive towards increase and decrease in fitness. LI Detector offers a tunable system that allows the user to identify small fitness effects with unprecedented sensitivity and specificity. LI Detector can be utilized to develop and refine gene-gene and gene-environment interaction networks of colony-forming organisms, including yeast, by increasing the range of fitness effects that can be reliably detected.

bioinformatics↗