Biology subjects

Stenberg, S.

Publications and source records attributed to Stenberg, S..

7 recordsLinked to original sources

bioRxiv2024

Predicting the natural yeast phenotypic landscape with machine learning

Most organisms traits result from the complex interplay of many genetic and environmental factors, making their prediction from genotypes difficult. Here, we used machine learning models to explore genotype-phenotype connections for 223 life history traits measured across 1011 genome-sequenced Saccharomyces cerevisiae strains. Firstly, we used genome-wide association studies to connect genetic variants with the phenotypes. Next, we benchmarked an automated machine learning pipeline that includes preprocessing, feature selection, and hyperparameters optimization in combination with multiple linear and complex machine learning methods. We determined gradient boosting machines as best performing in 65% of predictions and pangenome as best predictor, suggesting a considerable contribution of the accessory genome in controlling phenotypes. The accuracy broadly varied among the phenotypes (r = 0.2-0.9), consistent with varying levels of complexity, with stress resistance being easier to predict compared to growth across carbon and nitrogen nutrients. While no specific genomic features could be linked to the predictions for most phenotypes, machine learning identifies high-impact variants with established relationships to phenotypes despite being rare in the population. Near-perfect accuracies (r>0.95) were achieved when other phenomics data were used to aid predictions, suggesting shared useful information can be conveyed across phenotypes. Overall, our study underscores the power of machine learning to interpret the functional outcome of genetic variants.

genetics↗

bioRxiv2023

Genome instability footprint under rapamycin and hydroxyurea treatments

The mutational processes dictating the accumulation of mutations in genomes are shaped by genetic background, environment and their interactions. Accurate quantification of mutation rates and spectra under drugs has important implications in disease treatment. Here, we used whole-genome sequencing and time-resolved growth phenotyping of yeast mutation accumulation lines to give a detailed view of the mutagenic effects of rapamycin and hydroxyurea on the genome and cell growth. Mutation rates depended on the genetic backgrounds, but were only marginally affected by rapamycin. As a remarkable exception, rapamycin treatment was associated with frequent chromosome XII amplifications, which compensated for rapamycin induced rDNA repeat contraction on this chromosome and served to maintain rDNA content homeostasis and fitness. In hydroxyurea, a wide range of mutation rates were elevated regardless of the genetic backgrounds, with a particularly high occurrence of aneuploidy that associated with dramatic fitness loss. Hydroxyurea also induced a high T-to-G transversion rate that reversed the common G/C-to-A/T bias in yeast and gave rise to a broad range of structural variants, including mtDNA deletions. The hydroxyurea mutation footprint was consistent with the activation of error-prone DNA polymerase activities and non-homologues end joining repair pathways. Taken together, our study provides an in-depth view of mutation rates and signatures in rapamycin and hydroxyurea and their impact on cell fitness, which brings insights for assessing their chronic effects on genome integrity.

genomics↗

bioRxiv2022

Highly parallelized laboratory evolution of wine yeasts for enhanced metabolic phenotypes

Adaptive Laboratory Evolution (ALE) of microbes can improve the efficiency of sustainable industrial processes important to the global economy, but chance and genetic background effects often lead to suboptimal outcomes. Here we report an ALE platform to circumvent these flaws through parallelized clonal evolution at an unprecedented scale. Using this platform, we clonally evolved 104 yeast populations in parallel from many strains for eight desired wine production traits. Expansions of both ALE replicates and lineage numbers broadened the evolutionary search spectrum and increased the chances of evolving improved wine yeasts unencumbered by unwanted side effects. ALE gains often coincided with distinct aneuploidies and the emergence of semi-predictable side effects that were characteristic of each selection niche. Many high performing ALE strains retained their desired traits upon transfer to industrial conditions and produced high quality wine. Overall, our ALE platform brings evolutionary engineering into the realm of high throughput science and opens opportunities for rapidly optimizing microbes for use in many industrial sectors which otherwise could take many years to accomplish.

bioengineering↗

bioRxiv2022

Adaptation of the yeast gene knockout collection is near-perfectly predicted by fitness and diminishing return epistasis

Adaptive evolution of clonally dividing cells and microbes is the ultimate cause of cancer and infectious diseases. The possibility of constraining the adaptation of cell populations, by inhibiting proteins that enhance their evolvability has therefore attracted substantial interest. However, our current understanding of how individual genes influence the speed of adaptation is limited, partly because accurately tracking adaptation for many experimental cell populations in parallel is challenging. Here we use a high throughput artificial laboratory evolution (ALE) platform to track the adaptation of >18.000 cell populations corresponding to single gene deletion strains in the haploid yeast deletion collection. We report that the fitness of gene knockout near-perfectly (R2=0.91) predicts their adaptation dynamics under arsenic exposure, leaving virtually no role for dedicated evolvability functions in the corresponding proteins. We tracked the adaptation of another >23.000 yeast gene knockout populations to a diverse range of selection pressures and generalised the almost perfect (R2=0.72 to 0.98) capacity of initial fitness to predict the rate of adaptation. Finally, we reconstruct mutations in the genes FPS1, ASK10, and ARR3, which together account for almost all arsenic adaptation in wildtype cells, in gene deletions covering a broad fitness range. We show that the predictability of arsenic adaptation can be understood almost entirely as a global epistasis phenomenon where excluding arsenic from cells, through these mutations, is more beneficial in cells with low arsenic fitness regardless of what causes the arsenic defects. The lack of genes with a meaningful effect on the adaptation dynamics of clonally reproducing cell populations diminishes the prospects of developing adjuvant drugs aiming to slow antimicrobial and chemotherapy resistance.

evolutionary biology↗

bioRxiv2020

Aborting meiosis overcomes hybrid sterility

Hybrids between species or diverged lineages contain fundamentally novel genetic combinations but an impaired meiosis often makes them evolutionary dead ends. Here, we explored to what extent and how an aborted meiosis followed by a return-to-growth (RTG) promotes recombination across a panel of 20 yeast diploid backgrounds with different genomic structures and levels of sterility. Genome analyses of 284 clones revealed that RTG promoted recombination and generated extensive regions of loss-of-heterozygosity in sterile hybrids with either a defective meiosis or a heavily rearranged karyotype, whereas RTG recombination was reduced by high sequence divergence between parental subgenomes. The RTG recombination preferentially occurred in regions with local sequence homology and in meiotic recombination hotspots. The loss-of-heterozygosity had a profound impact on sexual and asexual fitness, and enabled genetic mapping of phenotypic differences in sterile lineages where linkage or association analyses failed. We propose that RTG gives sterile hybrids access to a natural route for genome recombination and adaptation. One sentence summaryAborting meiosis followed by a return to mitotic growth promotes evolution by genome wide-recombination in sterile yeast hybrids.

genetics↗

bioRxiv2020

Control of mitochondrial superoxide production includes programmed mtDNA deletion and restoration

Deletion of mitochondrial DNA in eukaryotes is mainly attributed to rare accidental events associated with mitochondrial replication or repair of double-strand breaks. We report the discovery that yeast cells arrest harmful intramitochondrial superoxide production by shutting down respiration through genetically controlled deletion of mitochondrial oxidative phosphorylation genes. We show that the regulatory circuitry underlying this editing critically involves the antioxidant enzyme superoxide dismutase 2 and two-way mitochondrial-nuclear communication. While mitochondrial DNA homeostasis is rapidly restored after cessation of a short-term superoxide stress, long-term stress causes maladaptive persistence of the deletion process, leading to complete annihilation of the cellular pool of intact mitochondrial genomes and irrevocable loss of respiratory ability. Our results may therefore be of etiological as well as therapeutic importance with regard to age-related mitochondrial impairment and disease. One-Sentence SummaryGenetically controlled editing of mitochondrial DNA is an integral part of the yeasts defenses against oxidative damage.

cell biology↗

bioRxiv2018

Conjugation factors controlling F-plasmid antibiotic resistance transmission

The rapid horizontal transmission of many antibiotic resistance genes between bacterial host cells on conjugative plasmids is a major cause of the accelerating antibiotic resistance crisis. Preventing understanding and targeting conjugation, there currently are no experimental platforms for fast and cost-efficient screening of genetic effects on antibiotic resistance transmission by conjugation. We introduce a novel experimental framework to screen for conjugation based horizontal transmission of antibiotic resistance between >60.000 pairs of cell populations in parallel. Plasmid-carrying donor strains are constructed in high throughput. We then mix the resistance plasmid carrying donors with recipients in a design where only transconjugants can reproduce, measure growth in dense intervals and extract transmission times as the growth lag. As proof-of-principle, we exhaustively explored chromosomal genes controlling F plasmid donation within E. coli populations, by screening the Keio deletion collection at high replication. We recover all six known chromosomal gene mutants affecting conjugation and identify >50 novel factors, all of which diminish antibiotic resistance transmission. We verify 10 of the novel genes effects in a liquid mating assay. The new framework holds great potential for exhaustive disclosing of candidate targets for helper drugs that delay resistance development in patients and societies and improves the longevity of current and future antibiotics.

microbiology↗