Genome-scale reconstruction of metabolic network in Bacillus subtilis based on high-throughput phenotyping and gene essentiality data

In this report, a genome-scale reconstruction of Bacillus subtilis metabolism and its iterative development based on the combination of genomic, biochemical, and physiological information and high-throughput phenotyping experiments is presented. The initial reconstruction was converted into an in silico model and expanded in a four-step iterative fashion. First, network gap analysis was used to identify 48 missing reactions that are needed for growth but were not found in the genome annotation. Second, the computed growth rates under aerobic conditions were compared with high-throughput phenotypic screen data, and the initial in silico model could predict the outcomes qualitatively in 140 of 271 cases considered. Detailed analysis of the incorrect predictions resulted in the addition of 75 reactions to the initial reconstruction, and 200 of 271 cases were correctly computed. Third, in silico computations of the growth phenotypes of knock-out strains were found to be consistent with experimental observations in 720 of 766 cases evaluated. Fourth, the integrated analysis of the large-scale substrate utilization and gene essentiality data with the genome-scale metabolic model revealed the requirement of 80 specific enzymes (transport, 53; intracellular reactions, 27) that were not in the genome annotation. Subsequent sequence analysis resulted in the identification of genes that could be putatively assigned to 13 intracellular enzymes. The final reconstruction accounted for 844 open reading frames and consisted of 1020 metabolic reactions and 988 metabolites. Hence, the in silico model can be used to obtain experimentally verifiable hypothesis on the metabolic functions of various genes.     

Genetic complexity and quantitative trait loci mapping of yeast morphological traits

Functional genomics relies on two essential parameters: the sensitivity of phenotypic measures and the power to detect genomic perturbations that cause phenotypic variations. In model organisms, two types of perturbations are widely used. Artificial mutations can be introduced in virtually any gene and allow the systematic analysis of gene function via mutants fitness. Alternatively, natural genetic variations can be associated to particular phenotypes via genetic mapping. However, the access to genome manipulation and breeding provided by model organisms is sometimes counterbalanced by phenotyping limitations. Here we investigated the natural genetic diversity of Saccharomyces cerevisiae cellular morphology using a very sensitive high-throughput imaging platform. We quantified 501 morphological parameters in over 50,000 yeast cells from a cross between two wild-type divergent backgrounds. Extensive morphological differences were found between these backgrounds. The genetic architecture of the traits was complex, with evidence of both epistasis and transgressive segregation. We mapped quantitative trait loci (QTL) for 67 traits and discovered 364 correlations between traits segregation and inheritance of gene expression levels. We validated one QTL by the replacement of a single base in the genome. This study illustrates the natural diversity and complexity of cellular traits among natural yeast strains and provides an ideal framework for a genetical genomics dissection of multiple traits. Our results did not overlap with results previously obtained from systematic deletion strains, showing that both approaches are necessary for the functional exploration of genomes.     

Oxidative stress-resistance assay for screening yeast strains overproducing heterologous proteins

Many natural proteins have been developed into drugs and produced for direct application. Identifying improved hosts to achieve high-level heterologous protein production is a challenge in the study of heterologous protein expression in recombinant yeast. In this study, a novel high-throughput assay to screen such overproducing Saccharomyces cerevisiae strains was systematically developed. The protocol designed was based on screening host strain derivatives with increased superoxide dismutase dependent resistance to oxidative stress. Yeast cells transformed with recombinant plasmid carrying SOD1 gene as a reporter responded exquisitely to oxidative stress induced by elevated concentrations of paraquat. Improved yeast strains resulting from screening clones subjected to genome shuffling through selective pressure argue for a more effective screening system compared with traditonal selection. Moreover, this approach can be employed in general biochemical analysis without utilization of flow cytometry or well plate reader. Therefore, it is expected that the high-throughput assay would make superior strains producing heterologous proteins.     

Important discoveries from analysing bacterial phenotypes

The ability to test hundreds to thousands of cellular phenotypes in a single experiment has opened up new avenues of investigation and exploration and led to important discoveries in very diverse applications of microbiological research and development. The information provided by global phenotyping is complementary to, and often more easily interpretable than information provided by global molecular analytical methods such as gene chips and proteomics. This report summarizes advances presented by scientists brought together to share their experiences and knowledge gained with high-throughput phenotyping.     

Multiple trait measurements in 43 inbred mouse strains capture the phenotypic diversity characteristic of human populations.

The breadth of genetic and phenotypic variation among inbred strains is often underappreciated because assessments include only a limited number of strains. Evaluation of a larger collection of inbred strains provides not only a greater understanding of this variation but collectively mimics much of the variation observed in human populations. We used a high-throughput phenotyping protocol to measure females and males of 43 inbred strains for body composition (weight, fat, lean tissue mass, and bone mineral density), plasma triglycerides, high-density lipoprotein and total cholesterol, glucose, insulin, and leptin levels while mice consumed a high-fat, high-cholesterol diet. Mice were fed a chow diet until they were 6-8 wk old and then fed the high-fat diet for an additional 18 wk. As expected, broad phenotypic diversity was observed among these strains. Significant variation between the sexes was also observed for most traits measured. Additionally, the response to the high-fat diet differed considerably among many strains. By the testing of such a large set of inbred strains for many traits, multiple phenotypes can be considered simultaneously and thereby aid in the selection of certain inbred strains as models for complex human diseases. These data are publicly available in the web-accessible Mouse Phenome Database (http://www.jax.org/phenome), an effort established to promote systematic characterization of biochemical and behavioral phenotypes of commonly used and genetically diverse inbred mouse strains. Data generated by this effort builds on the value of inbred mouse strains as a powerful tool for biomedical research.     

Implementation of the modified-SHIRPA protocol for screening of dominant phenotypes in a large-scale ENU mutagenesis program

SHIRPA is a three-stage protocol for the comprehensive assessment of primarily mouse behavior. The first stage consists of high-throughput phenotyping of 33 behavioral observations and 7 metabolic or disease observations. We modified this part of the protocol by integrating new morphologic observations into the initial phenotype assay of behavior and dysmorphology. Behavioral observations assessed by this protocol, now referred to as the “modified-SHIRPA,” are compatible with the original “SHIRPA” protocol. Using modified-SHIRPA, we screened dominant phenotypes of more than 10,000 G₁ progeny generated by crossing DBA/2J females with ENU-treated C57BL/6J males. To date, we have obtained 136 hereditary-confirmed mutants that exhibit behavioral and morphologic defects. Some independent mutant lines exhibited similar phenotypes, suggesting that they may represent alleles of the same gene or mutations in the same genetic pathway. They could hold great potential for the unraveling of the molecular mechanisms of certain phenotypes.     

Large-scale comparative phenotypic and genomic analyses reveal ecological preferences of shewanella species and identify metabolic pathways conserved at the genus level

The use of comparative genomics for the study of different microbiological species has increased substantially as sequence technologies become more affordable. However, efforts to fully link a genotype to its phenotype remain limited to the development of one mutant at a time. In this study, we provided a high-throughput alternative to this limiting step by coupling comparative genomics to the use of phenotype arrays for five sequenced Shewanella strains. Positive phenotypes were obtained for 441 nutrients (C, N, P, and S sources), with N-based compounds being the most utilized for all strains. Many genes and pathways predicted by genome analyses were confirmed with the comparative phenotype assay, and three degradation pathways believed to be missing in Shewanella were confirmed as missing. A number of previously unknown gene products were predicted to be parts of pathways or to have a function, expanding the number of gene targets for future genetic analyses. Ecologically, the comparative high-throughput phenotype analysis provided insights into niche specialization among the five different strains. For example, Shewanella amazonensis strain SB2B, isolated from the Amazon River delta, was capable of utilizing 60 C compounds, whereas Shewanella sp. strain W3-18-1, isolated from deep marine sediment, utilized only 25 of them. In spite of the large number of nutrient sources yielding positive results, our study indicated that except for the N sources, they were not sufficiently informative to predict growth phenotypes from increasing evolutionary distances. Our results indicate the importance of phenotypic evaluation for confirming genome predictions. This strategy will accelerate the functional discovery of genes and provide an ecological framework for microbial genome sequencing projects.     

High-throughput Phenotyping and Genomic Selection:The Frontiers of Crop Breeding Converge

Genomic selection (GS) and high-throughput phenotyping have recently been captivating the interest of the crop breeding com-munity from both the public and private sectors world-wide.Both approaches promise to revolutionize the prediction of complex traits,including growth,yield and adaptation to stress.Whereas high-throughput phenotyping may help to improve understanding of crop physiology,most powerful techniques for high-throughput field phenotyping are empirical rather than analytical and compa-rable to genomic selection.Despite the fact that the two method-ological approaches represent the extremes of what is understood as the breeding process (phenotype versus genome),they both consider the targeted traits (e.g.grain yield,growth,phenology,plant adaptation to stress) as a black box instead of dissecting them as a set of secondary traits (i.e.physiological) putatively related to the target trait.Both GS and high-throughput phenotyping have in common their empirical approach enabling breeders to use genome profile or phenotype without understanding the underlying biology.This short review discusses the main aspects of both approaches and focuses on the case of genomic selection of maize flowering traits and near-infrared spectroscopy (NIRS) and plant spectral reflectance as high-throughput field phenotyping methods for complex traits such as crop growth and yield.     

Oleaginous yeasts: Biodiversity and cultivation

Microbial lipids produced by oleaginous microorganisms, also called microbial oils and single cell oils (SCOs), are very promising sources for several oil industries. The exploration of efficient oleaginous yeast strains, meant to produce both high-quantity and high-quality lipids for the production of biodiesel, oleochemicals, and the other high value lipid products, have gained much attention. At present, the number of oleaginous yeast species that have been discovered is 8.2% of the total number of known yeast species, most of which have been isolated from their natural habitats. To explore high lipid producing yeasts, different methods, including high-throughput screening methods using colorimetric or fluorometric measures, have been developed. Understanding of the fatty acid composition profiles of lipids produced by oleaginous yeasts would help to define target lipid-related products. For lipid production, the employment of low-cost substrates suitable for yeast growth and lipid accumulation, and efficient cultivation processes are key factors for successfully increasing the amount of the accumulated lipid yield while decreasing the cost of production.     

Cryptococcus terricolus,an oleaginous yeast re-appraised

Summary Three strains of Cryptococcus terricolus have been examined for their ability to accumulate intra-cellular lipid. Of those only C. terricolus IFO 1322 was capable of accumulating substantial amounts (35–40% w/w) when cultivated in batch culture. The pattern of lipid accumulation was unusual in that the maximum rate of lipid synthesis was observed to occur during the exponential phase of growth when exogenous nitrogen was still available. Thus these results confirmed the earlier observations of Pedersen (1961; 1962a, b, c) that lipid levels in this organism were constitutively high. A preliminary biochemical analysis has failed to indicate why this unusual pattern of lipid accumulation occurs. The potential value of C. terricolus IFO 1322 for use in the production of single cell oil is discussed.     

LOW FREQUENCY OF MUTATIONS WITH STRONGLY DELETERIOUS BUT NONLETHAL FITNESS EFFECTS

Most experimentally detectable effects of mutations in cellular organisms are either lethal or mildly deleterious. A possible explanation for the paucity of strongly detrimental but nonlethal mutations is that the processes constituting cellular metabolism are either essential or largely redundant. Alternatively, the partition between lethal and inconspicuous mutations exists within important biological processes. To test this, we measured maximum growth rates of yeast strains each carrying the deletion of a single gene in one of 38 protein complexes. We also used relevant data from previous high-throughput phenotypic studies of the yeast gene-deletion collection. The complexes typified well-defined sets of genes engaged in a common process. Within virtually all essential complexes there were two clear modes of phenotypic effects, that is the cessation of growth or slowdown of growth by a few percent. This uniformity is striking given that complexes differ extensively in function, size, and proportion of essential proteins. The pattern of bimodality is observed both under optimal and suboptimal environmental conditions. The generic paucity of strong effects and abundance of small ones relates to the feasibility of analyses of quantitative traits and epidemiological surveys, irrespective of the particular element of metabolism under study.     

A new fluorescence-based method identifies protein phosphatases regulating lipid droplet metabolism

In virtually every cell, neutral lipids are stored in cytoplasmic structures called lipid droplets (LDs) and also referred to as lipid bodies or lipid particles. We developed a rapid high-throughput assay based on the recovery of quenched BODIPY-fluorescence that allows to quantify lipid droplets. The method was validated by monitoring lipid droplet turnover during growth of a yeast culture and by screening a group of strains deleted in genes known to be involved in lipid metabolism. In both tests, the fluorimetric assay showed high sensitivity and good agreement with previously reported data using microscopy. We used this method for high-throughput identification of protein phosphatases involved in lipid droplet metabolism. From 65 yeast knockout strains encoding protein phosphatases and its regulatory subunits, 13 strains revealed to have abnormal levels of lipid droplets, 10 of them having high lipid droplet content. Strains deleted for type I protein phosphatases and related regulators (ppz2, gac1, bni4), type 2A phosphatase and its related regulator (pph21 and sap185), type 2C protein phosphatases (ptc1, ptc4, ptc7) and dual phosphatases (pps1, msg5) were catalogued as high-lipid droplet content strains. Only reg1, a targeting subunit of the type 1 phosphatase Glc7p, and members of the nutrient-sensitive TOR pathway (sit4 and the regulatory subunit sap190) were catalogued as low-lipid droplet content strains, which were studied further. We show that Snf1, the homologue of the mammalian AMP-activated kinase, is constitutively phosphorylated (hyperactive) in sit4 and sap190 strains leading to a reduction of acetyl-CoA carboxylase activity. In conclusion, our fast and highly sensitive method permitted us to catalogue protein phosphatases involved in the regulation of LD metabolism and present evidence indicating that the TOR pathway and the SNF1/AMPK pathway are connected through the Sit4p-Sap190p pair in the control of lipid droplet biogenesis.     

Image-based cell phenotyping with deep learning

A cell's phenotype is the culmination of several cellular processes through a complex network of molecular interactions that ultimately result in a unique morphological signature. Visual cell phenotyping is the characterization and quantification of these observable cellular traits in images. Recently, cellular phenotyping has undergone a massive overhaul in terms of scale, resolution, and throughput, which is attributable to advances across electronic, optical, and chemical technologies for imaging cells. Coupled with the rapid acceleration of deep learning–based computational tools, these advances have opened up new avenues for innovation across a wide variety of high-throughput cell biology applications. Here, we review applications wherein deep learning is powering the recognition, profiling, and prediction of visual phenotypes to answer important biological questions. As the complexity and scale of imaging assays increase, deep learning offers computational solutions to elucidate the details of previously unexplored cellular phenotypes.     

Harnessing natural diversity to probe metabolic pathways

Analyses of cellular processes in the yeast Saccharomyces cerevisiae rely primarily upon a small number of highly domesticated laboratory strains, leaving the extensive natural genetic diversity of the model organism largely unexplored and unexploited. We asked if this diversity could be used to enrich our understanding of basic biological processes. As a test case, we examined a simple trait: the utilization of di/tripeptides as nitrogen sources. The capacity to import small peptides is likely to be under opposing selective pressures (nutrient utilization versus toxin vulnerability) and may therefore be sculpted by diverse pathways and strategies. Hitherto, dipeptide utilization in S. cerevisiae was solely ascribed to the activity of a single protein, the Ptr2p transporter. Using high-throughput phenotyping and several genetically diverse strains, we identified previously unknown cellular activities that contribute to this trait. We find that the Dal5p allantoate/ureidosuccinate permease is also capable of facilitating di/tripeptide transport. Moreover, even in the absence of Dal5p and Ptr2p, an additional activity—almost certainly the periplasmic asparaginase II Asp3p—facilitates the utilization of dipeptides with C-terminal asparagine residues by a different strategy. Another, as-yet-unidentified activity enables the utilization of dipeptides with C-terminal arginine residues. The relative contributions of these activities to the utilization of di/tripeptides vary among the strains analyzed, as does the vulnerability of these strains to a toxic dipeptide. Only by sampling the genetic diversity of multiple strains were we able to uncover several previously unrecognized layers of complexity in this metabolic pathway. High-throughput phenotyping facilitates the rapid exploration of the molecular basis of biological complexity, allowing for future detailed investigation of the selective pressures that drive microbial evolution.     

应用改良庆大霉素保护试验检测肠炎沙门氏菌侵袭力表型

肠炎血清型沙门氏菌 (Salmonella enterica serovar Enteritidis,SE) 是引起肠炎和全身感染重要的沙门氏菌血清型之一,了解沙门氏菌侵袭力表型对阐明其感染致病机制至关重要。传统庆大霉素保护试验 (GPA) 存在通量低、重复性差等缺点。文中利用96孔细胞培养和多孔道移液的高通量优势,结合菌落分区微量滴板计数法改良了传统GPA试验方案。应用改良的GPA方法检测了16株SE菌株对非吞噬细胞 (HT-29) 的入侵表型和43株SE菌株对吞噬细胞 (RAW264.7) 的胞内复制表型。通过比较分析SE强、弱菌株JL228和LN248对吞噬细胞 (RAW264.7) 的侵袭力表型发现,改良的GPA得出的数据组内和组间变异系数低、数据重复性强,胞内复制表型也与显微观察结果相符。通过实践应用发现,改良的GPA方法具有通量高、重复性强、结果可靠兼具省时、省力等优点,可作为沙门氏菌菌株侵袭力表型检测的更新方案,为进一步阐明其致病机制提供了更科学有效的方法。     

Prophage Excision Activates Listeria Competence Genes that Promote Phagosomal Escape and Virulence

Almost all eukaryotic genes are conserved, suggesting that they have essential functions. However, only a minority of genes have detectable loss-of-function phenotypes in experimental assays, and multiple theories have been proposed to explain this discrepancy. Here, we use RNA-mediated interference in C. elegans to examine how knockdown of any gene affects the overall fitness of worm populations. Whereas previous studies typically assess phenotypes that are detectable by eye after a single generation, we monitored growth quantitatively over several generations. In contrast to previous estimates, we find that, in these multigeneration population assays, the majority of genes affect fitness, and this suggests that genetic networks are not robust to mutation. Our results demonstrate that, in a single environmental condition, most animal genes play essential roles. This is a higher proportion than for yeast genes, and we suggest that the source of negative selection is different in animals and in unicellular eukaryotes.     

A hyper-recombination mutation in S. cerevisiae identifies a novel eukaryotic topoisomerase

A hyper-recombination mutation was isolated that causes an increase in recombination between short repeated delta sequences surrounding the SUP4-omicron gene in S. cerevisiae. The wild-type copy of this gene was cloned by complementation of one of its pleiotropic phenotypes, slow growth. DNA sequence of the clone revealed a 656 amino acid open reading frame capable of encoding a protein homologous to the bacterial type I topoisomerase. No homology was detected with previously identified eukaryotic topoisomerases. Construction of double mutants with either of the two known yeast topoisomerase genes revealed synergistic effects on growth suggesting overlapping functions. Expression of bacterial topoisomerase I in yeast can fully complement the slow growth defect of a null mutation. We have named this locus TOP3 and suggest that it defines a novel eukaryotic topoisomerase gene.     

Deletion of the Pichia pastoris KU70 homologue facilitates platform strain generation for gene expression and synthetic biology

Targeted gene replacement to generate knock-outs and knock-ins is a commonly used method to study the function of unknown genes. In the methylotrophic yeast Pichia pastoris, the importance of specific gene targeting has increased since the genome sequencing projects of the most commonly used strains have been accomplished, but rapid progress in the field has been impeded by inefficient mechanisms for accurate integration. To improve gene targeting efficiency in P. pastoris, we identified and deleted the P. pastoris KU70 homologue. We observed a substantial increase in the targeting efficiency using the two commonly known and used integration loci HIS4 and ADE1, reaching over 90% targeting efficiencies with only 250-bp flanking homologous DNA. Although the ku70 deletion strain was noted to be more sensitive to UV rays than the corresponding wild-type strain, no lethality, severe growth retardation or loss of gene copy numbers could be detected during repetitive rounds of cultivation and induction of heterologous protein production. Furthermore, we demonstrated the use of the ku70 deletion strain for fast and simple screening of genes in the search of new auxotrophic markers by targeting dihydroxyacetone synthase and glycerol kinase genes. Precise knock-out strains for the well-known P. pastoris AOX1, ARG4 and HIS4 genes and a whole series of expression vectors were generated based on the wild-type platform strain, providing a broad spectrum of precise tools for both intracellular and secreted production of heterologous proteins utilizing various selection markers and integration strategies for targeted or random integration of single and multiple genes. The simplicity of targeted integration in the ku70 deletion strain will further support protein production strain generation and synthetic biology using P. pastoris strains as platform hosts.