Reducing the vicissitudes of heterologous prochiral substrate catalysis by alcohol dehydrogenases through machine learning algorithms.

Alcohol dehydrogenases (ADHs) are popular catalysts for synthesizing chiral synthons a vital step for active pharmaceutical intermediate (API) production. They are grouped into three superfamilies namely, medium-chain (MDRs), short-chain dehydrogenase/reductases (SDRs), and iron-containing alcohol dehydrogenases. The former two are used extensively for producing various chiral synthons. Many studies screen multiple enzymes or engineer a specific enzyme for catalyzing a substrate of interest. These processes are resource-intensive and intricate. The current study attempts to decipher the ability to match different ADHs with their ideal substrates using machine learning algorithms. We explore the catalysis of 284 antibacterial ketone intermediates, against MDRs and SDRs to demonstrate a unique pattern of activity. To facilitate machine learning we curated a dataset comprising 33 features, encompassing 4 descriptors for each compound. Subsequently, an ensemble of machine learning techniques viz. Partial Least Squares (PLS) regression, k-Nearest Neighbors (kNN) regression, and Support Vector Machine (SVM) regression, was harnessed. Moreover, the assimilation of Principal Component Analysis (PCA) augmented precision and accuracy, thereby refining and demarcating diverse compound classes. As such, this classification is useful for discerning substrates amenable to diverse alcohol dehydrogenases, thereby mitigating the reliance on high-throughput screening or engineering in identifying the optimal enzyme for specific substrate.

Cell-type proteomic and metabolomic resolution of early and late grain filling stages of wheat endosperm.

The nutritional value of wheat grains, particularly their protein and metabolite composition, is a result of the grain-filling process, especially in the endosperm. Here, we employ laser microdissection (LMD) combined with shotgun proteomics and metabolomics to generate a cell type-specific proteome and metabolome inventory of developing wheat endosperm at the early (15 DAA) and late (26 DAA) grain-filling stages. We identified 1803 proteins and 41 metabolites from four different cell types (aleurone (AL), sub-aleurone (SA), starchy endosperm (SE) and endosperm transfer cells (ETCs). Differentially expressed proteins were detected, 67 in the AL, 31 in the SA, 27 in the SE and 50 in the ETCs between these two-time points. Cell-type accumulation of specific SUT and GLUT transporters, sucrose converting and starch biosynthesis enzymes correlate well with the respective sugar metabolites, suggesting sugar upload and starch accumulation via nucellar projection and ETC at 15 DAA in contrast to the later stage at 26 DAA. Changes in various protein levels between AL, SA and ETC support this metabolic switch from 15 to 26 DAA. The distinct spatial and temporal abundances of proteins and metabolites revealed a contrasting activity of nitrogen assimilation pathways, e.g. for GOGAT, GDH and glutamic acid, in the different cell types from 15 to 26 DAA, which can be correlated with specific protein accumulation in the endosperm. The integration of cell-type specific proteome and metabolome data revealed a complex metabolic interplay of the different cell types and a functional switch during grain development and grain-filling processes.

Natural variation in the chickpea metabolome under drought stress.

Chickpea is the world's fourth largest grown legume crop, which significantly contributes to food security by providing calories and dietary protein globally. However, the increased frequency of drought stress has significantly reduced chickpea production in recent years. Here, we have performed a field experiment with 36 diverse chickpea genotypes to evaluate grain yield, photosynthetic activities and molecular traits related to drought stress. For metabolomics analysis, leaf tissue was collected at three time points representing different pod-filling stages. We identified L-threonic acid, fructose and sugar alcohols involved in chickpea adaptive drought response within the mid-pod-filling stage. A stress susceptibility index for each genotype was calculated to identify tolerance capacity under drought, distributing the 36 genotypes into four categories from best to worst performance. To understand how biochemical mechanisms control different traits for genetic improvement, we performed a differential Jacobian analysis, which unveiled the interplay between various metabolic pathways across three time points, including higher flux towards inositol interconversions, glycolysis for high-performing genotypes, fumarate to malate conversion, and carbon and nitrogen metabolism perturbations. Metabolic GWAS (mGWAS) analysis uncovered gene candidates involved in glycolysis and MEP pathway corroborating with the differential biochemical Jacobian results. Accordingly, this proposed data analysis strategy bridges the gap from pure statistical association to causal biochemical relations by exploiting natural variation. Our study offers new perspectives on the genetic and metabolic understanding of drought tolerance-associated diversity in the chickpea metabolome and led to the identification of metabolic control points that can be also tested in other legume crops.

Accelerating wheat improvement through trait characterization: advances and perspectives.

Wheat (Triticum spp.) is a primary dietary staple food for humanity. Many wheat genetic resources with variable genomes have a record of domestication history and are widespread throughout the world. To develop elite wheat varieties, agronomical and stress-responsive trait characterization is foremost for evaluating existing germplasm to promote breeding. However, genomic complexity is one of the primary impediments to trait mining and characterization. Multiple reference genomes and cutting-edge technologies like haplotype mapping, genomic selection, precise gene editing tools, high-throughput phenotyping platforms, high-efficiency genetic transformation systems, and speed-breeding facilities are transforming wheat functional genomics research to understand the genomic diversity of polyploidy. This review focuses on the research achievements in wheat genomics, the available omics approaches, and bioinformatic resources developed in the past decades. Advances in genomics and system biology approaches are highlighted to circumvent bottlenecks in genomic and phenotypic selection, as well as gene transfer. In addition, we propose conducting precise functional genomic studies and developing sustainable breeding strategies for wheat. These developments in understanding wheat traits have speed up the creation of high-yielding, stress-resistant, and nutritionally enhanced wheat varieties, which will help in addressing global food security and agricultural sustainability in the era of climate change.

Low dose ribosomal DNA P-loop mutation affects development and enforces autophagy in Arabidopsis.

Arabidopsis contains hundreds of ribosomal DNA copies organized within the nucleolar organizing regions (NORs) in chromosomes 2 and 4. There are four major types of variants of rDNA, VAR1-4, based on the polymorphisms of 3' external transcribed sequences. The variants are known to be differentially expressed during plant development. We created a mutant by the CRISPR-Cas9-mediated excision of ~ 25 nt from predominantly NOR4 ribosomal DNA copies, obtaining mosaic mutational events on ~ 5% of all rDNA copies. The excised region consists of P-loop and Helix-82 segments of 25S rRNA. The mutation led to allelic, dosage-dependent defects marked by lateral root inhibition, reduced size, and pointy leaves, all previously observed for defective ribosomal function. The mutation in NOR4 led to dosage compensation from the NOR2 copies by elevated expression of VAR1 in mutants and further associated single-nucleotide variants, thus, resulting in altered rRNA sub-population. Furthermore, the mutants exhibited rRNA maturation defects specifically in the minor pathway typified by 32S pre-rRNA accumulation. Density-gradient fractionation and subsequent RT-PCR of rRNA analyses revealed that mutated copies were not incorporated into the translating ribosomes. The mutants in addition displayed an elevated autophagic flux as shown by the autophagic marker GFP-ATG8e, likely related to ribophagy.

A curated list of targeted optimized promiscuous ketoreductases (TOP-K).

Enzymes are either specific or promiscuous catalysts in nature. The latter is portrayed by protein families like CYP450Es, Aldo-ketoreductases and short/medium-chain dehydrogenases which participate in detoxification or secondary metabolite production. However, enzymes are evolutionarily 'blind' to an ever-increasing synthetic substrate library. Industries and laboratories have circumvented this by high-throughput screening or site-specific engineering to synthesize the product of interest. However, this paradigm entails cost and time-intensive one-enzyme, one-substrate catalysis model. One of the superfamilies regularly used for chiral alcohol synthesis are short-chain dehydrogenases/reductases (SDRs). Our objective is to determine a superset of promiscuous SDRs that can catalyze multiple ketones. They are typically classified into shorter 'Classical' and longer 'Extended' type ketoreductases. However, current analysis of modelled SDRs reveals a length-independent conserved N-terminus Rossmann-fold and a variable substrate-binding C-terminus substrate-binding region for both categories. The latter is recognized to influence the enzyme's flexibility and substrate promiscuity and we hypothesize these properties are directly linked with each other. We tested this by catalyzing ketone intermediates with the essential and specific enzyme: FabG_E, as well as non-essential SDRs such as UcpA and IdnO. The experimental results confirmed this biochemical-biophysical association, making it an interesting filter for ascertaining promiscuous enzymes. Hence, we created a dataset of physicochemical properties derived from the protein sequences and employed machine learning algorithms to examine potential candidates. This resulted in 24 targeted optimized ketoreductases (TOP-K) from 81 014 members. The experimental validation of select TOP-Ks demonstrated the correlation between the C-terminal lid-loop structure, enzyme flexibility and turnover rate on pro-pharmaceutical substrates.

Proteomics for abiotic stresses in legumes: present status and future directions.

Legumes are the most important crop plants in agriculture, contributing 27% of the world's primary food production. However, productivity and production of Legumes is reduced due to increasing environmental stress. Hence, there is a pressing need to understand the molecular mechanism involved in stress response and legumes adaptation. Proteomics provides an important molecular approach to investigate proteins involved in stress response. Both the gel-based and gel-free-based techniques have significantly contributed to understanding the proteome regulatory network in leguminous plants. In the present review, we have discussed the role of different proteomic approaches (2-DE, 2 D-DIGE, ICAT, iTRAQ, etc.) in the identification of various stress-responsive proteins in important leguminous crops, including soybean, chickpea, cowpea, pigeon pea, groundnut, and common bean under variable abiotic stresses including heat, drought, salinity, waterlogging, frost, chilling and metal toxicity. The proteomic analysis has revealed that most of the identified differentially expressed proteins in legumes are involved in photosynthesis, carbohydrate metabolism, signal transduction, protein metabolism, defense, and stress adaptation. The proteomic approaches provide insights in understanding the molecular mechanism of stress tolerance in legumes and have resulted in the identification of candidate genes used for the genetic improvement of plants against various environmental stresses. Identifying novel proteins and determining their expression under different stress conditions provide the basis for effective engineering strategies to improve stress tolerance in crop plants through marker-assisted breeding.

Industrial light at the end of the iron-containing (group III) alcohol dehydrogenase tunnel.

There are three prominent alcohol dehydrogenases superfamilies: short-chain, medium-chain, and iron-containing alcohol dehydrogenases (FeADHs). Many members are valuable catalysts for producing industrially relevant products such as active pharmaceutical intermediates, chiral synthons, biopolymers, biofuels, and secondary metabolites. However, FeADHs are the least explored enzymes among the superfamilies for commercial tenacities. They portray a conserved structure having a "tunnel-like" cofactor and substrate binding site with particular functions, despite representing high sequence diversity. Interestingly, phylogenetic analysis demarcates enzymes catalyzing distinct native substrates where closely related clades convert similar molecules. Further, homologs from various mesophilic and thermophilic microbes have been explored for designing a solvent and temperature-resistant enzyme for industrial purposes. The review explores different iron-containing alcohol dehydrogenases potential engineering of the enzymes and substrates helpful in manufacturing commercial products.

Spatial distribution of proteins and metabolites in developing wheat grain and their differential regulatory response during the grain filling process.

Grain filling and grain development are essential biological processes in the plant's life cycle, eventually contributing to the final seed yield and quality in all cereal crops. Studies of how the different wheat (Triticum aestivum L.) grain components contribute to the overall development of the seed are very scarce. We performed a proteomics and metabolomics analysis in four different developing components of the wheat grain (seed coat, embryo, endosperm, and cavity fluid) to characterize molecular processes during early and late grain development. In-gel shotgun proteomics analysis at 12, 15, 20, and 26 days after anthesis (DAA) revealed 15 484 identified and quantified proteins, out of which 410 differentially expressed proteins were identified in the seed coat, 815 in the embryo, 372 in the endosperm, and 492 in the cavity fluid. The abundance of selected protein candidates revealed spatially and temporally resolved protein functions associated with development and grain filling. Multiple wheat protein isoforms involved in starch synthesis such as sucrose synthases, starch phosphorylase, granule-bound and soluble starch synthase, pyruvate phosphate dikinase, 14-3-3 proteins as well as sugar precursors undergo a major tissue-dependent change in abundance during wheat grain development suggesting an intimate interplay of starch biosynthesis control. Different isoforms of the protein disulfide isomerase family as well as glutamine levels, both involved in the glutenin macropolymer pattern, showed distinct spatial and temporal abundance, revealing their specific role as indicators of wheat gluten quality. Proteins binned into the functional category of cell growth/division and protein synthesis/degradation were more abundant in the early stages (12 and 15 DAA). At the metabolome level all tissues and especially the cavity fluid showed highly distinct metabolite profiles. The tissue-specific data are integrated with biochemical networks to generate a comprehensive map of molecular processes during grain filling and developmental processes.

Heat stress response mechanisms in pollen development.

Being rooted in place, plants are faced with the challenge of responding to unfavourable local conditions. One such condition, heat stress, contributes massively to crop losses globally. Heatwaves are predicted to increase, and it is of vital importance to generate crops that are tolerant to not only heat stress but also to several other abiotic stresses (e.g. drought stress, salinity stress) to ensure that global food security is protected. A better understanding of the molecular mechanisms that underlie the temperature stress response in pollen will be a significant step towards developing effective breeding strategies for high and stable production in crop plants. While most studies have focused on the vegetative phase of plant growth to understand heat stress tolerance, it is the reproductive phase that requires more attention as it is more sensitive to elevated temperatures. Every phase of reproductive development is affected by environmental challenges, including pollen and ovule development, pollen tube growth, male-female cross-talk, fertilization, and embryo development. In this review we summarize how pollen is affected by heat stress and the molecular mechanisms employed during the stress period, as revealed by classical and -omics experiments.

PANOMICS meets germplasm.

Genotyping-by-sequencing has enabled approaches for genomic selection to improve yield, stress resistance and nutritional value. More and more resource studies are emerging providing 1000 and more genotypes and millions of SNPs for one species covering a hitherto inaccessible intraspecific genetic variation. The larger the databases are growing, the better statistical approaches for genomic selection will be available. However, there are clear limitations on the statistical but also on the biological part. Intraspecific genetic variation is able to explain a high proportion of the phenotypes, but a large part of phenotypic plasticity also stems from environmentally driven transcriptional, post-transcriptional, translational, post-translational, epigenetic and metabolic regulation. Moreover, regulation of the same gene can have different phenotypic outputs in different environments. Consequently, to explain and understand environment-dependent phenotypic plasticity based on the available genotype variation we have to integrate the analysis of further molecular levels reflecting the complete information flow from the gene to metabolism to phenotype. Interestingly, metabolomics platforms are already more cost-effective than NGS platforms and are decisive for the prediction of nutritional value or stress resistance. Here, we propose three fundamental pillars for future breeding strategies in the framework of Green Systems Biology: (i) combining genome selection with environment-dependent PANOMICS analysis and deep learning to improve prediction accuracy for marker-dependent trait performance; (ii) PANOMICS resolution at subtissue, cellular and subcellular level provides information about fundamental functions of selected markers; (iii) combining PANOMICS with genome editing and speed breeding tools to accelerate and enhance large-scale functional validation of trait-specific precision breeding.

Genomic footprints of repeated evolution of CAM photosynthesis in a Neotropical species radiation.

The adaptive radiation of Bromeliaceae (pineapple family) is one of the most diverse among Neotropical flowering plants. Diversification in this group was facilitated by shifts in several adaptive traits or "key innovations" including the transition from C3 to CAM photosynthesis associated with xeric (heat/drought) adaptation. We used phylogenomic approaches, complemented by differential gene expression (RNA-seq) and targeted metabolite profiling, to address the mechanisms of C3 /CAM evolution in the extremely species-rich bromeliad genus, Tillandsia, and related taxa. Evolutionary analyses of whole-genome sequencing and RNA-seq data suggest that evolution of CAM is associated with coincident changes to different pathways mediating xeric adaptation in this group. At the molecular level, C3 /CAM shifts were accompanied by gene expansion of XAP5 CIRCADIAN TIMEKEEPER homologs, a regulator involved in sugar- and light-dependent regulation of growth and development. Our analyses also support the re-programming of abscisic acid-related gene expression via differential expression of ABF2/ABF3 transcription factor homologs, and adaptive sequence evolution of an ENO2/LOS2 enolase homolog, effectively tying carbohydrate flux to abscisic acid-mediated abiotic stress response. By pinpointing different regulators of overlapping molecular responses, our results suggest plausible mechanistic explanations for the repeated evolution of correlated adaptive traits seen in a textbook example of an adaptive radiation.

Heat-Treatment-Responsive Proteins in Different Developmental Stages of Tomato Pollen Detected by Targeted Mass Accuracy Precursor Alignment (tMAPA).

Recently, we have developed a quantitative shotgun proteomics strategy called mass accuracy precursor alignment (MAPA). The MAPA algorithm uses high mass accuracy to bin mass-to-charge (m/z) ratios of precursor ions from LC-MS analyses, determines their intensities, and extracts a quantitative sample versus m/z ratio data alignment matrix from a multitude of samples. Here, we introduce a novel feature of this algorithm that allows the extraction and alignment of proteotypic peptide precursor ions or any other target peptide from complex shotgun proteomics data for accurate quantification of unique proteins. This strategy circumvents the problem of confusing the quantification of proteins due to indistinguishable protein isoforms by a typical shotgun proteomics approach. We applied this strategy to a comparison of control and heat-treated tomato pollen grains at two developmental stages, post-meiotic and mature. Pollen is a temperature-sensitive tissue involved in the reproductive cycle of plants and plays a major role in fruit setting and yield. By LC-MS-based shotgun proteomics, we identified more than 2000 proteins in total for all different tissues. By applying the targeted MAPA data-processing strategy, 51 unique proteins were identified as heat-treatment-responsive protein candidates. The potential function of the identified candidates in a specific developmental stage is discussed.

Characterization of Indian beers: chemical composition and antioxidant potential.

Chemical composition, antioxidant potential and corresponding lipid preoxidation of Indian commercial beers were evaluated. The presence of polyphenolic compounds such as tannic acid, gallic acid, catechol, vanillin, caffeic acid, quercetin, p-coumaric acid and rutin was quantified using LC-MS while the organic acids including tartaric, malic, acetic, citric and succinic acids were analysed using HPLC. Beer sample B8 had the greatest concentration of phenolic and flavonoid components (0.620 ± 0.084 mg/mL and 0.379 ± 0.020 mg/mL respectively) among the beer samples studied. The DPPH radical scavenging activity was observed in the range of 68.34 ± 0.85 % to 89.90 ± 0.71 % and ABTS radical cation scavenging activity was in the range of 59.75 ± 0.20 % to 76.22 ± 0.50 %. Percent protection in lipid peroxidation was quantified to be maximum (54.45 ± 3.39 %) in sample B5. Total phenolic content positively correlates with antioxidant assays, DPPH and ABTS (r = 0.35 and r = 0.58 respectively) with p < 0.001 and also with lipid peroxidation (r = 0.04) with p < 0.001. Negative correlation was observed between total flavonoid content with ABTS and lipid peroxidation (r = -0.1 and r = -0.05) respectively. The process of brewing warrants additional research to determine how the concentration of selected phenolic compounds can be increased.

Integrated multi-omics analysis reveals drought stress response mechanism in chickpea (Cicer arietinum L.).

Drought is one of the major constraints limiting chickpea productivity. To unravel complex mechanisms regulating drought response in chickpea, we generated transcriptomics, proteomics, and metabolomics datasets from root tissues of four contrasting drought-responsive chickpea genotypes: ICC 4958, JG 11, and JG 11+ (drought-tolerant), and ICC 1882 (drought-sensitive) under control and drought stress conditions. Integration of transcriptomics and proteomics data identified enriched hub proteins encoding isoflavone 4'-O-methyltransferase, UDP-d-glucose/UDP-d-galactose 4-epimerase, and delta-1-pyrroline-5-carboxylate synthetase. These proteins highlighted the involvement of pathways such as antibiotic biosynthesis, galactose metabolism, and isoflavonoid biosynthesis in activating drought stress response mechanisms. Subsequently, the integration of metabolomics data identified six metabolites (fructose, galactose, glucose, myoinositol, galactinol, and raffinose) that showed a significant correlation with galactose metabolism. Integration of root-omics data also revealed some key candidate genes underlying the drought-responsive "QTL-hotspot" region. These results provided key insights into complex molecular mechanisms underlying drought stress response in chickpea.

Comparative analysis of geotypic variations in the proteome of Nostoc commune.

Cyanobacterium Nostoc commune is a filamentous terrestrial prokaryotic organism widely distributed, which suggest its high adaptive potential to environmental or abiotic stress. Physiological parameters and proteomic analysis were performed in two accession of N. commune with the aim to elucidate the differences of physiological trails between distant geotypes, namely Antarctic (AN) and central European (CE). The result obtained clearly showed that the AN geotype demonstrates elevated levels of total phenols, flavonoids, carotenoids, and phycobiliproteins, indicative of its adaptation to environmental stress as referred by comparison to CE sample. Additionally, we employed LC-MS analysis to investigate the proteomes of N. commune from AN and CE geotypes. In total, 1147 proteins were identified, among which 646 proteins expressed significant (up-regulation) changes in both accessions. In the AN geotype, 83 exclusive proteins were identified compared to 25 in the CE geotype. Functional classification of the significant proteins showed a large fraction involved in photosynthesis, amino acid metabolism, carbohydrate metabolism and protein biosynthesis. Further analysis revealed some defense-related proteins such as, superoxide dismutase (SOD) and glutathione reductase, which are rather explicitly expressed in the AN N. commune. The last two proteins suggest a more stressful condition in AN N. commune. In summary, our findings highlight biochemical processes that safeguard the AN geotype of N. commune from extreme environmental challenges, not recorded in CE accession, probably due to less stressful environment in Europe. This study brings the first ever proteomic analysis of N. commune, emphasizing the need for additional investigations into the climate adaptation of this species with rather plastic genome.

PANOMICS at the interface of root-soil microbiome and BNI.

Nitrification and denitrification are soil biological processes responsible for large nitrogen losses from agricultural soils and generation of the greenhouse gas (GHG) N2O. Increased use of nitrogen fertilizer and the resulting decline in nitrogen use efficiency (NUE) are a major concern in agroecosystems. This nitrogen cycle in the rhizosphere is influenced by an intimate soil microbiome-root exudate interaction and biological nitrification inhibition (BNI). A PANOMICS approach can dissect these processes. We review breakthroughs in this area, including identification and characterization of root exudates by metabolomics and proteomics, which facilitate better understanding of belowground chemical communications and help identify new biological nitrification inhibitors (BNIs). We also address challenges for advancing the understanding of the role root exudates play in biotic and abiotic stresses.

Quantifying the impact of dynamic plant-environment interactions on metabolic regulation.

A plant's genome encodes enzymes, transporters and many other proteins which constitute metabolism. Interactions of plants with their environment shape their growth, development and resilience towards adverse conditions. Although genome sequencing technologies and applications have experienced triumphantly rapid development during the last decades, enabling nowadays a fast and cheap sequencing of full genomes, prediction of metabolic phenotypes from genotype × environment interactions remains, at best, very incomplete. The main reasons are a lack of understanding of how different levels of molecular organisation depend on each other, and how they are constituted and expressed within a setup of growth conditions. Phenotypic plasticity, e.g., of the genetic model plant Arabidopsis thaliana, has provided important insights into plant-environment interactions and the resulting genotype x phenotype relationships. Here, we summarize previous and current findings about plant development in a changing environment and how this might be shaped and reflected in metabolism and its regulation. We identify current challenges in the study of plant development and metabolic regulation and provide an outlook of how methodological workflows might support the application of findings made in model systems to crops and their cultivation.

Ferroptosis is the key cellular process mediating Bisphenol A responses in Chlamydomonas and a promising target for enhancing microalgae-based bioremediation.

Microplastics are one of the major pollutants in aquatic environments. Among their components, Bisphenol A (BPA) is one of the most abundant and dangerous, leading to endocrine disorders deriving even in different types of cancer in mammals. However, despite this evidence, the xenobiotic effects of BPA over plantae and microalgae still need to be better understood at the molecular level. To fill this gap, we characterized the physiological and proteomic response of Chlamydomonas reinhardtii during long-term BPA exposure by analyzing physiological and biochemical parameters combined with proteomics. BPA imbalanced iron and redox homeostasis, disrupting cell function and triggering ferroptosis. Intriguingly, this microalgae defense against this pollutant is recovering at both molecular and physiological levels while starch accumulation at 72 h of BPA exposure. In this work, we addressed the molecular mechanisms involved in BPA exposure, demonstrating for the first time the induction of ferroptosis in a eukaryotic alga and how ROS detoxification mechanisms and other specific proteomic rearrangements reverted this situation. These results are of great significance not only for understanding the BPA toxicology or exploring the molecular mechanisms of ferroptosis in microalgae but also for defining novel target genes for microplastic bioremediation efficient strain development.