PRECOG: a tool for automated extraction and visualization of fitness components in microbial growth phenomics

gcplyr: an R package for microbial growth curve data analysis

BACKGROUND

Characterization of microbial growth is of both fundamental and applied interest. Modern platforms can automate collection of high-throughput microbial growth curves, necessitating the development of computational tools to handle and analyze these data to produce insights.

RESULTS

To address this need, here I present a newly-developed R package: gcplyr. gcplyr can flexibly import growth curve data in common tabular formats, and reshapes it under a tidy framework that is flexible and extendable, enabling users to design custom analyses or plot data with popular visualization packages. gcplyr can also incorporate metadata and generate or import experimental designs to merge with data. Finally, gcplyr carries out model-free (non-parametric) analyses. These analyses do not require mathematical assumptions about microbial growth dynamics, and gcplyr is able to extract a broad range of important traits, including growth rate, doubling time, lag time, maximum density and carrying capacity, diauxie, area under the curve, extinction time, and more.

CONCLUSIONS

gcplyr makes scripted analyses of growth curve data in R straightforward, streamlines common data wrangling and analysis steps, and easily integrates with common visualization and statistical analyses.

Ancient and recent origins of shared polymorphisms in yeast

Shared genetic polymorphisms between populations and species can be ascribed to ancestral variation or to more recent gene flow. Here, we mapped shared polymorphisms in Saccharomyces cerevisiae and its sister species Saccharomyces paradoxus, which diverged 4-6 million years ago. We used a dense map of single-nucleotide diagnostic markers (mean distance 15.6 base pairs) in 1,673 sequenced S. cerevisiae isolates to catalogue 3,852 sequence blocks (≥5 consecutive markers) introgressed from S. paradoxus, with most being recent and clade-specific. The highly diverged wild Chinese S. cerevisiae lineages were depleted of introgressed blocks but retained an excess of individual ancestral polymorphisms derived from incomplete lineage sorting, perhaps due to less dramatic population bottlenecks. In the non-Chinese S. cerevisiae lineages, we inferred major hybridization events and detected cases of overlapping introgressed blocks across distinct clades due to either shared histories or convergent evolution. We experimentally engineered, in otherwise isogenic backgrounds, the introgressed PAD1-FDC1 gene pair that independently arose in two S. cerevisiae clades and revealed that it increases resistance against diverse antifungal drugs. Overall, our study retraces the histories of divergence and secondary contacts across S. cerevisiae and S. paradoxus populations and unveils a functional outcome.

Engineering Saccharomyces cerevisiae for targeted hydrolysis and fermentation of glucuronoxylan through CRISPR/Cas9 genome editing

BACKGROUND

The abundance of glucuronoxylan (GX) in agricultural and forestry residual side streams positions it as a promising feedstock for microbial conversion into valuable compounds. By engineering strains of the widely employed cell factory Saccharomyces cerevisiae with the ability to directly hydrolyze and ferment GX polymers, we can avoid the need for harsh chemical pretreatments and costly enzymatic hydrolysis steps prior to fermentation. However, for an economically viable bioproduction process, the engineered strains must efficiently express and secrete enzymes that act in synergy to hydrolyze the targeted polymers.

RESULTS

The aim of this study was to equip the xylose-fermenting S. cerevisiae strain CEN.PK XXX with xylanolytic enzymes targeting beechwood GX. Using a targeted enzyme approach, we matched hydrolytic enzyme activities to the chemical features of the GX substrate and determined that besides endo-1,4-β-xylanase and β-xylosidase activities, α-methyl-glucuronidase activity was of great importance for GX hydrolysis and yeast growth. We also created a library of strains expressing different combinations of enzymes, and screened for yeast strains that could express and secrete the enzymes and metabolize the GX hydrolysis products efficiently. While strains engineered with BmXyn11A xylanase and XylA β-xylosidase could grow relatively well in beechwood GX, strains further engineered with Agu115 α-methyl-glucuronidase did not display an additional growth benefit, likely due to inefficient expression and secretion of this enzyme. Co-cultures of strains expressing complementary enzymes as well as external enzyme supplementation boosted yeast growth and ethanol fermentation of GX, and ethanol titers reached a maximum of 1.33 g L- 1 after 48 h under oxygen limited condition in bioreactor fermentations.

CONCLUSION

This work underscored the importance of identifying an optimal enzyme combination for successful engineering of S. cerevisiae strains that can hydrolyze and assimilate GX. The enzymes must exhibit high and balanced activities, be compatible with the yeast's expression and secretion system, and the nature of the hydrolysis products must be such that they can be taken up and metabolized by the yeast. The engineered strains, particularly when co-cultivated, display robust growth and fermentation of GX, and represent a significant step forward towards a sustainable and cost-effective bioprocessing of GX-rich biomass. They also provide valuable insights for future strain and process development targets.

High Expression of ENO1 and Low Levels of Circulating Anti-ENO1 Autoantibodies in Patients with Myelodysplastic Neoplasms and Acute Myeloid Leukaemia

In solid tumours, high expression of the glycolytic enzyme, α-enolase (ENO1), predicts for poor patient overall survival (OS), and circulating autoantibodies to ENO1 correlate positively with diagnosis and negatively with advanced disease. Although ENO1 is one of the most highly expressed genes in acute myeloid leukaemia (AML), its potential role as a biomarker in AML or its precursor, myelodysplastic neoplasms (MDS), has not been investigated. A meta-analysis of nine AML online datasets (n = 1419 patients) revealed that high ENO1 expression predicts for poor OS (HR = 1.22, 95% CI: 1.10-1.34, p < 0.001). Additionally, when compared to AML in remission (n = 5), ENO1 protein detected by immunohistochemistry was significantly higher at diagnosis in bone marrow from both AML (n = 5, p < 0.01) and MDS patients (n = 12, p < 0.05), and did not correlate with percentage of blasts (r = 0.28, p = 0.21). AML patients (n = 34) had lower circulating levels of ENO1 autoantibodies detected by ELISA compared to 26 MDS and 18 controls (p = 0.003). However, there was no difference in OS between AML patients with high vs. low levels of anti-ENO1 autoantibodies (p = 0.77). BM immunostaining for ENO1 and patient monitoring of anti-ENO1 autoantibody levels may be useful biomarkers for MDS and AML.

Selective Bias Virtual Screening for Discovery of Promising Antimalarial Candidates targeting Plasmodium N-Myristoyltransferase

Malaria remains a significant public health challenge, with Plasmodium vivax being the species responsible for the most prevalent form of the disease. Given the limited therapeutic options available, the search for new antimalarials against P. vivax is urgent. This study aims to identify new inhibitors for P. vivax N-myristoyltransferase (PvNMT), an essential drug target against malaria. Through a validated virtual screening campaign, we prioritized 23 candidates for further testing. In the yeast NMT system, seven compounds exhibit a potential inhibitor phenotype. In vitro antimalarial phenotypic assays confirmed the activity of four candidates while demonstrating an absence of cytotoxicity. Enzymatic assays reveal LabMol-394 as the most promising inhibitor, displaying selectivity against the parasite and a strong correlation within the yeast system. Furthermore, molecular dynamics simulations shed some light into its binding mode. This study constitutes a substantial contribution to the exploration of a selective quinoline scaffold and provides valuable insights into the development of new antimalarial candidates.

Building synthetic chromosomes from natural DNA

De novo chromosome synthesis is costly and time-consuming, limiting its use in research and biotechnology. Building synthetic chromosomes from natural components is an unexplored alternative with many potential applications. In this paper, we report CReATiNG (Cloning, Reprogramming, and Assembling Tiled Natural Genomic DNA), a method for constructing synthetic chromosomes from natural components in yeast. CReATiNG entails cloning segments of natural chromosomes and then programmably assembling them into synthetic chromosomes that can replace the native chromosomes in cells. We use CReATiNG to synthetically recombine chromosomes between strains and species, to modify chromosome structure, and to delete many linked, non-adjacent regions totaling 39% of a chromosome. The multiplex deletion experiment reveals that CReATiNG also enables recovery from flaws in synthetic chromosome design via recombination between a synthetic chromosome and its native counterpart. CReATiNG facilitates the application of chromosome synthesis to diverse biological problems.

Parsley: a web app for parsing data from plate readers

SUMMARY

As demand for the automation of biological assays has increased over recent years, the range of measurement types implemented by multiwell plate readers has broadened and the list of published software packages that caters to their analysis has grown. However, most plate readers export data in esoteric formats with little or no metadata, while most analytical software packages are built to work with tidy data accompanied by associated metadata. 'Parser' functions are therefore required to prepare raw data for analysis. Such functions are instrument- and data type-specific, and to date, no generic tool exists that can parse data from multiple data types or multiple plate readers, despite the potential for such a tool to speed up access to analysed data and remove an important barrier for less confident coders. We have developed the interactive web application, Parsley, to bridge this gap. Unlike conventional programmatic parser functions, Parsley makes few assumptions about exported data, instead employing user inputs to identify and extract data from data files. In doing so, it is designed to enable any user to parse plate reader data and can handle a wide variety of instruments (10+) and data types (53+). Parsley is freely available via a web interface, enabling access to its unique plate reader data parsing functionality, without the need to install software or write code.

AVAILABILITY AND IMPLEMENTATION

The Parsley web application can be accessed at: https://gbstan.shinyapps.io/parsleyapp/. The source code is available at: https://github.com/ec363/parsleyapp and is archived on Zenodo: https://zenodo.org/records/10011752.

The construction and optimization of engineered yeast chassis for efficient biosynthesis of 8-hydroxygeraniol

Microbial production of monoterpenoid indole alkaloids (MIAs) provides a sustainable and eco-friendly means to obtain compounds with high pharmaceutical values. However, efficient biosynthesis of MIAs in heterologous microorganisms is hindered due to low supply of key precursors such as geraniol and its derivative 8-hydroxygeraniol catalyzed by geraniol 8-hydroxylase (G8H). In this study, we developed a facile evolution platform to screen strains with improved yield of geraniol by using the SCRaMbLE system embedded in the Sc2.0 synthetic yeast and confirmed the causal role of relevant genomic targets. Through genome mining, we identified several G8H enzymes that perform much better than the commonly used CrG8H for 8-hydroxygeraniol production in vivo. We further showed that the N-terminus of these G8H enzymes plays an important role in cellular activity by swapping experiments. Finally, the combination of the engineered chassis, optimized biosynthesis pathway, and utilization of G8H led to the final strain with more than 30-fold improvement in producing 8-hydroxygeraniol compared with the starting strain. Overall, this study will provide insights into the construction and optimization of yeast cells for efficient biosynthesis of 8-hydroxygeraniol and its derivatives.

A robust yeast biocontainment system with two-layered regulation switch dependent on unnatural amino acid

Synthetic auxotrophy in which cell viability depends on the presence of an unnatural amino acid (unAA) provides a powerful strategy to restrict unwanted propagation of genetically modified organisms (GMOs) in open environments and potentially prevent industrial espionage. Here, we describe a generic approach for robust biocontainment of budding yeast dependent on unAA. By understanding escape mechanisms, we specifically optimize our strategies by introducing designed "immunity" to the generation of amber-suppressor tRNAs and developing the transcriptional- and translational-based biocontainment switch. We further develop a fitness-oriented screening method to easily obtain multiplex safeguard strains that exhibit robust growth and undetectable escape frequency (<~10-9) on solid media for 14 days. Finally, we show that employing our multiplex safeguard system could restrict the proliferation of strains of interest in a real fermentation scenario, highlighting the great potential of our yeast biocontainment strategy to protect the industrial proprietary strains.

System-wide optimization of an orthogonal translation system with enhanced biological tolerance

Over the past two decades, synthetic biological systems have revolutionized the study of cellular physiology. The ability to site-specifically incorporate biologically relevant non-standard amino acids using orthogonal translation systems (OTSs) has proven particularly useful, providing unparalleled access to cellular mechanisms modulated by post-translational modifications, such as protein phosphorylation. However, despite significant advances in OTS design and function, the systems-level biology of OTS development and utilization remains underexplored. In this study, we employ a phosphoserine OTS (pSerOTS) as a model to systematically investigate global interactions between OTS components and the cellular environment, aiming to improve OTS performance. Based on this analysis, we design OTS variants to enhance orthogonality by minimizing host process interactions and reducing stress response activation. Our findings advance understanding of system-wide OTS:host interactions, enabling informed design practices that circumvent deleterious interactions with host physiology while improving OTS performance and stability. Furthermore, our study emphasizes the importance of establishing a pipeline for systematically profiling OTS:host interactions to enhance orthogonality and mitigate mechanisms underlying OTS-mediated host toxicity.

A high-throughput yeast approach to characterize aquaporin permeabilities: Profiling the Arabidopsis PIP aquaporin sub-family

INTRODUCTION

Engineering membrane transporters to achieve desired functionality is reliant on availability of experimental data informing structure-function relationships and intelligent design. Plant aquaporin (AQP) isoforms are capable of transporting diverse substrates such as signaling molecules, nutrients, metalloids, and gases, as well as water. AQPs can act as multifunctional channels and their transport function is reliant on many factors, with few studies having assessed transport function of specific isoforms for multiple substrates.

METHODS

High-throughput yeast assays were developed to screen for transport function of plant AQPs, providing a platform for fast data generation and cataloguing of substrate transport profiles. We applied our high-throughput growth-based yeast assays to screen all 13 Arabidopsis PIPs (AtPIPs) for transport of water and several neutral solutes: hydrogen peroxide (H2O2), boric acid (BA), and urea. Sodium (Na+) transport was assessed using elemental analysis techniques.

RESULTS

All AtPIPs facilitated water and H2O2 transport, although their growth phenotypes varied, and none were candidates for urea transport. For BA and Na+ transport, AtPIP2;2 and AtPIP2;7 were the top candidates, with yeast expressing these isoforms having the most pronounced toxicity response to BA exposure and accumulating the highest amounts of Na+. Linking putative AtPIP isoform substrate transport profiles with phylogenetics and gene expression data, enabled us to align possible substrate preferences with known and hypothesized biological roles of AtPIPs.

DISCUSSION

This testing framework enables efficient cataloguing of putative transport functionality of diverse AQPs at a scale that can help accelerate our understanding of AQP biology through big data approaches (e.g. association studies). The principles of the individual assays could be further adapted to test additional substrates. Data generated from this framework could inform future testing of AQP physiological roles, and address knowledge gaps in structure-function relationships to improve engineering efforts.

Growth Rate Evaluation of the Budding Yeast Saccharomyces cerevisiae Cells Carrying Endogenously Expressed Fluorescent Protein Fusions

Fluorescent proteins within fluorescent fusions have been reported to affect cellular growth fitness via altering native protein function and intracellular localization. Here we report in detail a procedure to analyze the growth characteristics of yeast cells expressing such fusions in comparison to unmodified parental strain. This approach can serve as an initial step in fluorescent protein characterization in vivo.

Using colony size to measure fitness in Saccharomyces cerevisiae

Competitive fitness assays in liquid culture have been a mainstay for characterizing experimental evolution of microbial populations. Growth of microbial strains has also been extensively characterized by colony size and could serve as a useful alternative if translated to per generation measurements of relative fitness. To examine fitness based on colony size, we established a relationship between cell number and colony size for strains of Saccharomyces cerevisiae robotically pinned onto solid agar plates in a high-density format. This was used to measure growth rates and estimate relative fitness differences between evolved strains and their ancestors. After controlling for edge effects through both normalization and agar-trimming, we found that colony size is a sensitive measure of fitness, capable of detecting 1% differences. While fitnesses determined from liquid and solid mediums were not equivalent, our results demonstrate that colony size provides a sensitive means of measuring fitness that is particularly well suited to measurements across many environments.

Increasing Ethanol Tolerance and Ethanol Production in an Industrial Fuel Ethanol Saccharomyces cerevisiae Strain

The stress imposed by ethanol to Saccharomyces cerevisiae cells are one of the most challenging limiting factors in industrial fuel ethanol production. Consequently, the toxicity and tolerance to high ethanol concentrations has been the subject of extensive research, allowing the identification of several genes important for increasing the tolerance to this stress factor. However, most studies were performed with well-characterized laboratory strains, and how the results obtained with these strains work in industrial strains remains unknown. In the present work, we have tested three different strategies known to increase ethanol tolerance by laboratory strains in an industrial fuel–ethanol producing strain: the overexpression of the TRP1 or MSN2 genes, or the overexpression of a truncated version of the MSN2 gene. Our results show that the industrial CAT-1 strain tolerates up to 14% ethanol, and indeed the three strategies increased its tolerance to ethanol. When these strains were subjected to fermentations with high sugar content and cell recycle, simulating the industrial conditions used in Brazilian distilleries, only the strain with overexpression of the truncated MSN2 gene showed improved fermentation performance, allowing the production of 16% ethanol from 33% of total reducing sugars present in sugarcane molasses. Our results highlight the importance of testing genetic modifications in industrial yeast strains under industrial conditions in order to improve the production of industrial fuel ethanol by S. cerevisiae.

Aborting meiosis allows recombination in sterile diploid yeast hybrids

Hybrids between diverged lineages contain novel genetic combinations but an impaired meiosis often makes them evolutionary dead ends. Here, we explore to what extent an aborted meiosis followed by a return-to-growth (RTG) promotes recombination across a panel of 20 Saccharomyces cerevisiae and S. paradoxus diploid hybrids with different genomic structures and levels of sterility. Genome analyses of 275 clones reveal that RTG promotes recombination and generates extensive regions of loss-of-heterozygosity in sterile hybrids with either a defective meiosis or a heavily rearranged karyotype, whereas RTG recombination is reduced by high sequence divergence between parental subgenomes. The RTG recombination preferentially arises in regions with low local heterozygosity and near meiotic recombination hotspots. The loss-of-heterozygosity has a profound impact on sexual and asexual fitness, and enables genetic mapping of phenotypic differences in sterile lineages where linkage analysis would fail. We propose that RTG gives sterile yeast hybrids access to a natural route for genome recombination and adaptation.

A CRISPR Interference Screen of Essential Genes Reveals that Proteasome Regulation Dictates Acetic Acid Tolerance in Saccharomyces cerevisiae

CRISPR interference (CRISPRi) is a powerful tool to study cellular physiology under different growth conditions, and this technology provides a means for screening changed expression of essential genes. In this study, a Saccharomyces cerevisiae CRISPRi library was screened for growth in medium supplemented with acetic acid. Acetic acid is a growth inhibitor challenging the use of yeast for the industrial conversion of lignocellulosic biomasses. Tolerance to acetic acid that is released during biomass hydrolysis is crucial for cell factories to be used in biorefineries. The CRISPRi library screened consists of >9,000 strains, where >98% of all essential and respiratory growth-essential genes were targeted with multiple guide RNAs (gRNAs). The screen was performed using the high-throughput, high-resolution Scan-o-matic platform, where each strain is analyzed separately. Our study identified that CRISPRi targeting of genes involved in vesicle formation or organelle transport processes led to severe growth inhibition during acetic acid stress, emphasizing the importance of these intracellular membrane structures in maintaining cell vitality. In contrast, strains in which genes encoding subunits of the 19S regulatory particle of the 26S proteasome were downregulated had increased tolerance to acetic acid, which we hypothesize is due to ATP salvage through an increased abundance of the 20S core particle that performs ATP-independent protein degradation. This is the first study where high-resolution CRISPRi library screening paves the way to understanding and bioengineering the robustness of yeast against acetic acid stress.

IMPORTANCE Acetic acid is inhibitory to the growth of the yeast Saccharomyces cerevisiae, causing ATP starvation and oxidative stress, which leads to the suboptimal production of fuels and chemicals from lignocellulosic biomass. In this study, where each strain of a CRISPRi library was characterized individually, many essential and respiratory growth-essential genes that regulate tolerance to acetic acid were identified, providing a new understanding of the stress response of yeast and new targets for the bioengineering of industrial yeast. Our findings on the fine-tuning of the expression of proteasomal genes leading to increased tolerance to acetic acid suggest that this could be a novel strategy for increasing stress tolerance, leading to improved strains for the production of biobased chemicals.

Comparison of endogenously expressed fluorescent protein fusions behaviour for protein quality control and cellular ageing research

The yeast Hsp104 protein disaggregase is often used as a reporter for misfolded or damaged protein aggregates and protein quality control and ageing research. Observing Hsp104 fusions with fluorescent proteins is a popular approach to follow post stress protein aggregation, inclusion formation and disaggregation. While concerns that bigger protein tags, such as genetically encoded fluorescent tags, may affect protein behaviour and function have been around for quite some time, experimental evidence of how exactly the physiology of the protein of interest is altered within fluorescent protein fusions remains limited. To address this issue, we performed a comparative assessment of endogenously expressed Hsp104 fluorescent fusions function and behaviour. We provide experimental evidence that molecular behaviour may not only be altered by introducing a fluorescent protein tag but also varies depending on such a tag within the fusion. Although our findings are especially applicable to protein quality control and ageing research in yeast, similar effects may play a role in other eukaryotic systems.

sparse-growth-curve: a Computational Pipeline for Parsing Cellular Growth Curves with Low Temporal Resolution

Here, we introduce a Python-based repository, sparse-growth-curve, a software package designed for parsing cellular growth curves with low temporal resolution. The repository uses cell density and time data as the input, automatically separates different growth phases, calculates the exponential growth rates, and produces multiple graphs to aid in interpretation.

A yeast chemogenomic screen identifies pathways that modulate adipic acid toxicity

Adipic acid production by yeast fermentation is gaining attention as a renewable source of platform chemicals for making nylon products. However, adipic acid toxicity inhibits yeast growth and fermentation. Here, we performed a chemogenomic screen in Saccharomyces cerevisiae to understand the cellular basis of adipic acid toxicity. Our screen revealed that KGD1 (a key gene in the tricarboxylic acid cycle) deletion improved tolerance to adipic acid and its toxic precursor, catechol. Conversely, disrupting ergosterol biosynthesis as well as protein trafficking and vacuolar transport resulted in adipic acid hypersensitivity. Notably, we show that adipic acid disrupts the Membrane Compartment of Can1 (MCC) on the plasma membrane and impacts endocytosis. This was evidenced by the rapid internalization of Can1 for vacuolar degradation. As ergosterol is an essential component of the MCC and protein trafficking mechanisms are required for endocytosis, we highlight the importance of these cellular processes in modulating adipic acid toxicity.

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Deletion of the TCA cycle gene KGD1 improves tolerance to adipic acid and catechol

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Ergosterol and Pdr12 play non-overlapping roles protecting cell from adipic acid

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Adipic acid-induced plasma membrane localization of Pdr12 is independent of ergosterol

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Adipic acid disrupts the Membrane Compartment of Can1 (MCC) and induces endocytosis

Correlative single-molecule fluorescence barcoding of gene regulation in Saccharomyces cerevisiae

Most cells adapt to their environment by switching combinations of genes on and off through a complex interplay of transcription factor proteins (TFs). The mechanisms by which TFs respond to signals, move into the nucleus and find specific binding sites in target genes is still largely unknown. Single-molecule fluorescence microscopes, which can image single TFs in live cells, have begun to elucidate the problem. Here, we show that different environmental signals, in this case carbon sources, yield a unique single-molecule fluorescence pattern of foci of a key metabolic regulating transcription factor, Mig1, in the nucleus of the budding yeast, Saccharomyces cerevisiae. This pattern serves as a 'barcode' of the gene regulatory state of the cells which can be correlated with cell growth characteristics and other biological function.

A CRISPR activation and interference toolkit for industrial Saccharomyces cerevisiae strain KE6-12

Recent advances in CRISPR/Cas9 based genome editing have considerably advanced genetic engineering of industrial yeast strains. In this study, we report the construction and characterization of a toolkit for CRISPR activation and interference (CRISPRa/i) for a polyploid industrial yeast strain. In the CRISPRa/i plasmids that are available in high and low copy variants, dCas9 is expressed alone, or as a fusion with an activation or repression domain; VP64, VPR or Mxi1. The sgRNA is introduced to the CRISPRa/i plasmids from a double stranded oligonucleotide by in vivo homology-directed repair, allowing rapid transcriptional modulation of new target genes without cloning. The CRISPRa/i toolkit was characterized by alteration of expression of fluorescent protein-encoding genes under two different promoters allowing expression alterations up to ~ 2.5-fold. Furthermore, we demonstrated the usability of the CRISPRa/i toolkit by improving the tolerance towards wheat straw hydrolysate of our industrial production strain. We anticipate that our CRISPRa/i toolkit can be widely used to assess novel targets for strain improvement and thus accelerate the design-build-test cycle for developing various industrial production strains.

Pyphe, a python toolbox for assessing microbial growth and cell viability in high-throughput colony screens

Microbial fitness screens are a key technique in functional genomics. We present an all-in-one solution, pyphe, for automating and improving data analysis pipelines associated with large-scale fitness screens, including image acquisition and quantification, data normalisation, and statistical analysis. Pyphe is versatile and processes fitness data from colony sizes, viability scores from phloxine B staining or colony growth curves, all obtained with inexpensive transilluminating flatbed scanners. We apply pyphe to show that the fitness information contained in late endpoint measurements of colony sizes is similar to maximum growth slopes from time series. We phenotype gene-deletion strains of fission yeast in 59,350 individual fitness assays in 70 conditions, revealing that colony size and viability provide complementary, independent information. Viability scores obtained from quantifying the redness of phloxine-stained colonies accurately reflect the fraction of live cells within colonies. Pyphe is user-friendly, open-source and fully documented, illustrated by applications to diverse fitness analysis scenarios.

Discordant evolution of mitochondrial and nuclear yeast genomes at population level

Background

Mitochondria are essential organelles partially regulated by their own genomes. The mitochondrial genome maintenance and inheritance differ from the nuclear genome, potentially uncoupling their evolutionary trajectories. Here, we analysed mitochondrial sequences obtained from the 1011 Saccharomyces cerevisiae strain collection and identified pronounced differences with their nuclear genome counterparts.

Results

In contrast with pre-whole genome duplication fungal species, S. cerevisiae mitochondrial genomes show higher genetic diversity compared to the nuclear genomes. Strikingly, mitochondrial genomes appear to be highly admixed, resulting in a complex interconnected phylogeny with a weak grouping of isolates, whereas interspecies introgressions are very rare. Complete genome assemblies revealed that structural rearrangements are nearly absent with rare inversions detected. We tracked intron variation in COX1 and COB to infer gain and loss events throughout the species evolutionary history. Mitochondrial genome copy number is connected with the nuclear genome and linearly scale up with ploidy. We observed rare cases of naturally occurring mitochondrial DNA loss, petite, with a subset of them that do not suffer the expected growth defect in fermentable rich media.

Conclusions

Overall, our results illustrate how differences in the biology of two genomes coexisting in the same cells can lead to discordant evolutionary histories.

Emerging Technologies in Algal Biotechnology: Toward the Establishment of a Sustainable, Algae-Based Bioeconomy

Mankind has recognized the value of land plants as renewable sources of food, medicine, and materials for millennia. Throughout human history, agricultural methods were continuously modified and improved to meet the changing needs of civilization. Today, our rapidly growing population requires further innovation to address the practical limitations and serious environmental concerns associated with current industrial and agricultural practices. Microalgae are a diverse group of unicellular photosynthetic organisms that are emerging as next-generation resources with the potential to address urgent industrial and agricultural demands. The extensive biological diversity of algae can be leveraged to produce a wealth of valuable bioproducts, either naturally or via genetic manipulation. Microalgae additionally possess a set of intrinsic advantages, such as low production costs, no requirement for arable land, and the capacity to grow rapidly in both large-scale outdoor systems and scalable, fully contained photobioreactors. Here, we review technical advancements, novel fields of application, and products in the field of algal biotechnology to illustrate how algae could present high-tech, low-cost, and environmentally friendly solutions to many current and future needs of our society. We discuss how emerging technologies such as synthetic biology, high-throughput phenomics, and the application of internet of things (IoT) automation to algal manufacturing technology can advance the understanding of algal biology and, ultimately, drive the establishment of an algal-based bioeconomy.

Interactively AUDIT Your Growth Curves with a Suite of R Packages

Bottlenecks often occur during data analysis when studying microbial growth in liquid culture at large scale. A researcher can collect thousands of growth curves, repeated measures of a microbial liquid culture, at once in multiple micro titer plates by purpose-built robotic instruments. However, it can be difficult and time-consuming to inspect and analyze these data. This is especially true for researchers without programming experience. To enable this researcher, we created and describe an interactive application: Automated Usher for Data Inspection and Tidying (AUDIT). It allows the user to analyze growth curve data generated from one or more runs each with one or more micro titer plates alongside their experimental design. AUDIT covers input, pre-processing, summarizing, visual exploration and output. Compared to previously available tools AUDIT handles more data, provides live previews and is built from individually re-usable pieces distributed as R packages.

Improving Chromosome Synthesis with a Semiquantitative Phenotypic Assay and Refined Assembly Strategy

Recent advances in DNA synthesis technology have made it possible to rewrite the entire genome of an organism. The major hurdles in this process are efficiently identifying and fixing the defect-inducing sequences (or "bugs") during rewriting. Here, we describe a high-throughput, semiquantitative phenotype assay for evaluating the fitness of synthetic yeast and identifying potential bugs. Growth curves were measured under a carefully chosen set of testing conditions. Statistical analysis revealed strains with subtle defects relative to the wild type, which were targeted for debugging. The effectiveness of the assay was demonstrated by phenotypic profiling of all intermediate synthetic strains of the synthetic yeast chromosome XII. Subsequently, the assay was applied during the process of constructing another synthetic chromosome. Furthermore, we designed an efficient chromosome assembly strategy that integrates iterative megachunk construction with CRISPR/Cas9-mediated assembly of synthetic segments. Together, the semiquantitative assay and refined assembly strategy could greatly facilitate synthetic genomics projects by improving efficiency during both debugging and construction.

ERO1α promotes hypoxic tumor progression and is associated with poor prognosis in pancreatic cancer

Pancreatic cancer is a leading cause of mortality worldwide due to the difficulty of detecting early-stage disease and our poor understanding of the mediators that drive progression of hypoxic solid tumors. We therefore used a heavy isotope 'pulse/trace' proteomic approach to determine how hypoxia (Hx) alters pancreatic tumor expression of proteins that confer treatment resistance, promote metastasis, and suppress host immunity. Using this method, we identified that hypoxia stress stimulates pancreatic cancer cells to rapidly translate proteins that enhance metastasis (NOTCH2, NCS1, CD151, NUSAP1), treatment resistance (ABCB6), immune suppression (NFIL3, WDR4), angiogenesis (ANGPT4, ERO1α, FOS), alter cell metabolic activity (HK2, ENO2), and mediate growth-promoting cytokine responses (CLK3, ANGPTL4). Database mining confirmed that elevated gene expression of these hypoxia-induced mediators is significantly associated with poor patient survival in various stages of pancreatic cancer. Among these proteins, the oxidoreductase enzyme ERO1α was highly sensitive to induction by hypoxia stress across a range of different pancreatic cancer cell lines and was associated with particularly poor prognosis in human patients. Consistent with these data, genetic deletion of ERO1α substantially reduced growth rates and colony formation by pancreatic cancer cells when assessed in a series of functional assays in vitro. Accordingly, when transferred into a mouse xenograft model, ERO1α-deficient tumor cells exhibited severe growth restriction and negligible disease progression in vivo. Together, these data indicate that ERO1α is potential prognostic biomarker and novel drug target for pancreatic cancer therapy.

The fission yeast FHIT homolog affects checkpoint control of proliferation and is regulated by mitochondrial electron transport

Genetic analysis has strongly implicated human FHIT (Fragile Histidine Triad) as a tumor suppressor gene, being mutated in a large proportion of early‐stage cancers. The functions of the FHIT protein have, however, remained elusive. Here, we investigated aph1⁺, the fission yeast homolog of FHIT, for functions related to checkpoint control and oxidative metabolism. In sublethal concentrations of DNA damaging agents, aph1Δ mutants grew with a substantially shorter lag phase. In aph1Δ mutants carrying a hypomorphic allele of cds1 (the fission yeast homolog of Chk2), in addition, increased chromosome fragmentation and missegregation were found. We also found that under hypoxia or impaired electron transport function, the Aph1 protein level was strongly depressed. Previously, FHIT has been linked to regulation of the human 9‐1‐1 checkpoint complex constituted by Hus1, Rad1, and Rad9. In Schizosaccharomyces pombe, the levels of all three 9‐1‐1 proteins are all downregulated by hypoxia in similarity with Aph1. Moreover, deletion of the aph1⁺ gene reduced the Rad1 protein level, indicating a direct relationship between these two proteins. We conclude that the fission yeast FHIT homolog has a role in modulating DNA damage checkpoint function, possibly through an effect on the 9‐1‐1 complex, and that this effect may be critical under conditions of limiting oxidative metabolism and reoxygenation.

Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales

Pre-existing and de novo genetic variants can both drive adaptation to environmental changes, but their relative contributions and interplay remain poorly understood. Here we investigated the evolutionary dynamics in drug-treated yeast populations with different levels of pre-existing variation by experimental evolution coupled with time-resolved sequencing and phenotyping. We found a doubling of pre-existing variation alone boosts the adaptation by 64.1% and 51.5% in hydroxyurea and rapamycin, respectively. The causative pre-existing and de novo variants were selected on shared targets: RNR4 in hydroxyurea and TOR1, TOR2 in rapamycin. Interestingly, the pre-existing and de novo TOR variants map to different functional domains and act via distinct mechanisms. The pre-existing TOR variants from two domesticated strains exhibited opposite rapamycin resistance effects, reflecting lineage-specific functional divergence. This study provides a dynamic view on how pre-existing and de novo variants interactively drive adaptation and deepens our understanding of clonally evolving populations.

TARBP2-mediated destabilization of Nanog overcomes sorafenib resistance in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a lethal human malignancy and a leading cause of cancer‐related death worldwide. Patients with HCC are often diagnosed at an advanced stage, and the prognosis is usually poor. The multikinase inhibitor sorafenib is the first‐line treatment for patients with advanced HCC. However, cases of primary or acquired resistance to sorafenib have gradually increased, leading to a predicament in HCC therapy. Thus, it is critical to investigate the mechanism underlying sorafenib resistance. Transactivation response element RNA‐binding protein 2 (TARBP2) is a multifaceted miRNA biogenesis factor that regulates cancer stem cell (CSC) properties. The tumorigenicity and drug resistance of cancer cells are often enhanced due to the acquisition of CSC features. However, the role of TARBP2 in sorafenib resistance in HCC remains unknown. Our results demonstrate that TARBP2 is significantly downregulated in sorafenib‐resistant HCC cells. The TARBP2 protein was destabilized through autophagic–lysosomal proteolysis, thereby stabilizing the expression of the CSC marker protein Nanog, which facilitates sorafenib resistance in HCC cells. In summary, here we reveal a novel miRNA‐independent role of TARBP2 in regulating sorafenib resistance in HCC cells.

Yeast chemogenomic screen identifies distinct metabolic pathways required to tolerate exposure to phenolic fermentation inhibitors ferulic acid, 4-hydroxybenzoic acid and coniferyl aldehyde

The conversion of plant material into biofuels and high value products is a two-step process of hydrolysing plant lignocellulose and next fermenting the sugars produced. However, lignocellulosic hydrolysis not only frees sugars for fermentation it simultaneously generates toxic chemicals, including phenolic compounds which severely inhibit yeast fermentation. To understand the molecular basis of phenolic compound toxicity, we performed genome-wide chemogenomic screens in Saccharomyces cerevisiae to identify deletion mutants that were either hypersensitive or resistant to three common phenolic compounds found in plant hydrolysates: coniferyl aldehyde, ferulic acid and 4-hydroxybenzoic acid. Despite being similar in structure, our screen revealed that yeast utilizes distinct pathways to tolerate phenolic compound exposure. Furthermore, although each phenolic compound induced reactive oxygen species (ROS), ferulic acid and 4-hydroxybenzoic acid-induced a general cytoplasmic ROS distribution while coniferyl aldehyde-induced ROS partially localized to the mitochondria and to a lesser extent, the endoplasmic reticulum. We found that the glucose-6-phosphate dehydrogenase enzyme Zwf1, which catalyzes the rate limiting step of pentose phosphate pathway, is required for reducing the accummulation of coniferyl aldehyde-induced ROS, potentially through the sequestering of Zwf1 to sites of ROS accumulation. Our novel insights into biological impact of three common phenolic inhibitors will inform the engineering of yeast strains with improved efficiency of biofuel and biochemical production in the presence hydrolysate-derived phenolic compounds.

Growth of a common planktonic diatom quantified using solid medium culturing

The ability to grow on solid culture medium is a pre-requisite for a successful microbial genetic model organism. Skeletonema marinoi, a bloom-forming, planktonic marine microalga, is widely used in ecological, evolutionary and population genetics studies. We have tested and confirmed the ability of this common organism to grow on solid culture medium (agar) under experimentally manipulated conditions. We established a protocol for quantifying growth characteristics - length of lag phase, growth rate, maximum biomass yield - on agar medium. The procedure was tested under experimental treatments and the resulting growth changes correlated with those observed in standard liquid culture. The ability to grow on solid medium broadens the use of S. marinoi as a molecular model, where agar is routinely used for various purposes (growth, selection, storage); and the possibility to quantify colony growth opens the way for high throughput, automated, or semi-automated phenotyping solutions.

Yeast diversity in relation to the production of fuels and chemicals

In addition to ethanol, yeasts have the potential to produce many other industrially-relevant chemicals from numerous different carbon sources. However there remains a paucity of information about overall capability across the yeast family tree. Here, 11 diverse species of yeasts with genetic backgrounds representative of different branches of the family tree were investigated. They were compared for their abilities to grow on a range of sugar carbon sources, to produce potential platform chemicals from such substrates and to ferment hydrothermally pretreated rice straw under simultaneous saccharification and fermentation conditions. The yeasts differed considerably in their metabolic capabilities and production of ethanol. A number could produce significant amounts of ethyl acetate, arabinitol, glycerol and acetate in addition to ethanol, including from hitherto unreported carbon sources. They also demonstrated widely differing efficiencies in the fermentation of sugars derived from pre-treated rice straw biomass and differential sensitivities to fermentation inhibitors. A new catabolic property of Rhodotorula mucilaginosa (NCYC 65) was discovered in which sugar substrate is cleaved but the products are not metabolised. We propose that engineering this and some of the other properties discovered in this study and transferring such properties to conventional industrial yeast strains could greatly expand their biotechnological utility.

Contrasting evolutionary genome dynamics between domesticated and wild yeasts

Structural rearrangements have long been recognized as an important source of genetic variation, with implications in phenotypic diversity and disease, yet their detailed evolutionary dynamics remain elusive. Here we use long-read sequencing to generate end-to-end genome assemblies for 12 strains representing major subpopulations of the partially domesticated yeast Saccharomyces cerevisiae and its wild relative Saccharomyces paradoxus. These population-level high-quality genomes with comprehensive annotation enable precise definition of chromosomal boundaries between cores and subtelomeres and a high-resolution view of evolutionary genome dynamics. In chromosomal cores, S. paradoxus shows faster accumulation of balanced rearrangements (inversions, reciprocal translocations and transpositions), whereas S. cerevisiae accumulates unbalanced rearrangements (novel insertions, deletions and duplications) more rapidly. In subtelomeres, both species show extensive interchromosomal reshuffling, with a higher tempo in S. cerevisiae. Such striking contrasts between wild and domesticated yeasts are likely to reflect the influence of human activities on structural genome evolution.

High-throughput system-wide engineering and screening for microbial biotechnology

Genetic engineering and screening of large number of cells or populations is a crucial bottleneck in today's systems biology and applied (micro)biology. Instead of using standard methods in bottles, flasks or 96-well plates, scientists are increasingly relying on high-throughput strategies that miniaturize their experiments to the nanoliter and picoliter scale and the single-cell level. In this review, we summarize different high-throughput system-wide genome engineering and screening strategies for microbes. More specifically, we will emphasize the use of multiplex automated genome evolution (MAGE) and CRISPR/Cas systems for high-throughput genome engineering and the application of (lab-on-chip) nanoreactors for high-throughput single-cell or population screening.

Disentangling genetic and epigenetic determinants of ultrafast adaptation

A major rationale for the advocacy of epigenetically mediated adaptive responses is that they facilitate faster adaptation to environmental challenges. This motivated us to develop a theoretical-experimental framework for disclosing the presence of such adaptation-speeding mechanisms in an experimental evolution setting circumventing the need for pursuing costly mutation-accumulation experiments. To this end, we exposed clonal populations of budding yeast to a whole range of stressors. By growth phenotyping, we found that almost complete adaptation to arsenic emerged after a few mitotic cell divisions without involving any phenotypic plasticity. Causative mutations were identified by deep sequencing of the arsenic-adapted populations and reconstructed for validation. Mutation effects on growth phenotypes, and the associated mutational target sizes were quantified and embedded in data-driven individual-based evolutionary population models. We found that the experimentally observed homogeneity of adaptation speed and heterogeneity of molecular solutions could only be accounted for if the mutation rate had been near estimates of the basal mutation rate. The ultrafast adaptation could be fully explained by extensive positive pleiotropy such that all beneficial mutations dramatically enhanced multiple fitness components in concert. As our approach can be exploited across a range of model organisms exposed to a variety of environmental challenges, it may be used for determining the importance of epigenetic adaptation-speeding mechanisms in general.