Dissecting the genetic architecture of root-related traits in a grafted wild Vitis berlandieri population for grapevine rootstock breeding.

In woody perennial plants, quantitative genetics and association studies remain scarce for root-related traits, due to the time required to obtain mature plants and the complexity of phenotyping. In grapevine, a grafted cultivated plant, most of the rootstocks used are hybrids between American Vitis species (V. rupestris, V. riparia, and V. berlandieri). In this study, we used a wild population of an American Vitis species (V. berlandieri) to analyze the genetic architecture of the root-related traits of rootstocks in a grafted context. We studied a population consisting of 211 genotypes, with one to five replicates each (n = 846 individuals), plus four commercial rootstocks as control genotypes (110R, 5BB, Börner, and SO4). After two independent years of experimentation, the best linear unbiased estimates method revealed root-related traits with a moderate-to-high heritability (0.36-0.82) and coefficient of genetic variation (0.15-0.45). A genome-wide association study was performed with the BLINK model, leading to the detection of 11 QTL associated with four root-related traits (one QTL was associated with the total number of roots, four were associated with the number of small roots (< 1 mm in diameter), two were associated with the number of medium-sized roots (1 mm < diameter < 2 mm), and four were associated with mean diameter) accounting for up to 25.1% of the variance. Three genotypes were found to have better root-related trait performances than the commercial rootstocks and therefore constitute possible new candidates for use in grapevine rootstock breeding programs.

Genetic structure and first genome-wide insights into the adaptation of a wild relative of grapevine, Vitis berlandieri.

In grafted plants, such as grapevine, increasing the diversity of rootstocks available to growers is an ideal strategy for helping plants to adapt to climate change. The rootstocks used for grapevine are hybrids of various American Vitis, including V. berlandieri. The rootstocks currently use in vineyards are derived from breeding programs involving very small numbers of parental individuals. We investigated the structure of a natural population of V. berlandieri and the association of genetic diversity with environmental variables. In this study, we collected seeds from 78 wild V. berlandieri plants in Texas after open fertilization. We genotyped 286 individuals to describe the structure of the population, and environmental information collected at the sampling site made it possible to perform genome-environment association analysis (GEA). De novo long-read whole-genome sequencing was performed on V. berlandieri and a STRUCTURE analysis was performed. We identified and filtered 104,378 SNPs. We found that there were two subpopulations associated with differences in elevation, temperature, and rainfall between sampling sites. GEA identified three QTL for elevation and 15 QTL for PCA coordinates based on environmental parameter variability. This original study is the first GEA study to be performed on a population of grapevines sampled in natural conditions. Our results shed new light on rootstock genetics and could open up possibilities for introducing greater diversity into genetic improvement programs for grapevine rootstocks.

Towards grapevine root architectural models to adapt viticulture to drought.

To sustainably adapt viticultural production to drought, the planting of rootstock genotypes adapted to a changing climate is a promising means. Rootstocks contribute to the regulation of scion vigor and water consumption, modulate scion phenological development and determine resource availability by root system architecture development. There is, however, a lack of knowledge on spatio-temporal root system development of rootstock genotypes and its interactions with environment and management that prevents efficient knowledge transfer into practice. Hence, winegrowers take only limited advantage of the large variability of existing rootstock genotypes. Models of vineyard water balance combined with root architectural models, using both static and dynamic representations of the root system, seem promising tools to match rootstock genotypes to frequently occurring future drought stress scenarios and address scientific knowledge gaps. In this perspective, we discuss how current developments in vineyard water balance modeling may provide the background for a better understanding of the interplay of rootstock genotypes, environment and management. We argue that root architecture traits are key drivers of this interplay, but our knowledge on rootstock architectures in the field remains limited both qualitatively and quantitatively. We propose phenotyping methods to help close current knowledge gaps and discuss approaches to integrate phenotyping data into different models to advance our understanding of rootstock x environment x management interactions and predict rootstock genotype performance in a changing climate. This could also provide a valuable basis for optimizing breeding efforts to develop new grapevine rootstock cultivars with optimal trait configurations for future growing conditions.

Variability of Constitutive Stilbenoid Levels and Profiles in Grape Cane (Vitis vinifera L.) Depending upon Variety and Clone, Location in the Vineyard, Pruning Time, and Vintage.

Stilbenoids in grape cane (Vitis vinifera L.) are bioactive compounds relevant for plant defense and the potential valorization of this byproduct. Our screening of grape cane from 102 varieties showed constitutive stilbenoid levels in a wide range (557-7748 mg/kg of dry weight). Analyses of genetically distinct clones of selected cultivars unraveled that intravarietal variability (e.g., cv. Riesling, 3236-6541 mg/kg) was higher than that across samples from a single clone but different vineyard positions (3017-3710 mg/kg). Furthermore, stilbenoid levels in samples obtained in October, December, and February (3 years, 2017-2019) showed pronounced quantitative and qualitative variability and the highest yields upon December pruning. For instance, vitisin B and ε-viniferin in cv. Pinot Noir and Accent were predominant in 2017 and 2019 (both >90% of total stilbenoids) but not in 2018 (both <55%) when temperatures were high and precipitation low. In brief, we report the variability of stilbenoid levels in grape cane depending upon genetic and environmental factors.

A Regulatory Science Initiative to Harmonize and Standardize Digital Pathology and Machine Learning Processes to Speed up Clinical Innovation to Patients.

Unlocking the full potential of pathology data by gaining computational access to histological pixel data and metadata (digital pathology) is one of the key promises of computational pathology. Despite scientific progress and several regulatory approvals for primary diagnosis using whole-slide imaging, true clinical adoption at scale is slower than anticipated. In the U.S., advances in digital pathology are often siloed pursuits by individual stakeholders, and to our knowledge, there has not been a systematic approach to advance the field through a regulatory science initiative. The Alliance for Digital Pathology (the Alliance) is a recently established, volunteer, collaborative, regulatory science initiative to standardize digital pathology processes to speed up innovation to patients. The purpose is: (1) to account for the patient perspective by including patient advocacy; (2) to investigate and develop methods and tools for the evaluation of effectiveness, safety, and quality to specify risks and benefits in the precompetitive phase; (3) to help strategize the sequence of clinically meaningful deliverables; (4) to encourage and streamline the development of ground-truth data sets for machine learning model development and validation; and (5) to clarify regulatory pathways by investigating relevant regulatory science questions. The Alliance accepts participation from all stakeholders, and we solicit clinically relevant proposals that will benefit the field at large. The initiative will dissolve once a clinical, interoperable, modularized, integrated solution (from tissue acquisition to diagnostic algorithm) has been implemented. In times of rapidly evolving discoveries, scientific input from subject-matter experts is one essential element to inform regulatory guidance and decision-making. The Alliance aims to establish and promote synergistic regulatory science efforts that will leverage diverse inputs to move digital pathology forward and ultimately improve patient care.

Digital Imaging and Communications in Medicine Whole Slide Imaging Connectathon at Digital Pathology Association Pathology Visions 2017.

As digital pathology systems for clinical diagnostic work applications become mainstream, interoperability between these systems from different vendors becomes critical. For the first time, multiple digital pathology vendors have publicly revealed the use of the digital imaging and communications in medicine (DICOM) standard file format and network protocol to communicate between separate whole slide acquisition, storage, and viewing components. Note the use of DICOM for clinical diagnostic applications is still to be validated in the United States. The successful demonstration shows that the DICOM standard is fundamentally sound, though many lessons were learned. These lessons will be incorporated as incremental improvements in the standard, provide more detailed profiles to constrain variation for specific use cases, and offer educational material for implementers. Future Connectathon events will expand the scope to include more devices and vendors, as well as more ambitious use cases including laboratory information system integration and annotation for image analysis, as well as more geographic diversity. Users should request DICOM features in all purchases and contracts. It is anticipated that the growth of DICOM-compliant manufacturers will likely also ease DICOM for pathology becoming a recognized standard and as such the regulatory pathway for digital pathology products.

BioPreDyn-bench: a suite of benchmark problems for dynamic modelling in systems biology.

BACKGROUND: Dynamic modelling is one of the cornerstones of systems biology. Many research efforts are currently being invested in the development and exploitation of large-scale kinetic models. The associated problems of parameter estimation (model calibration) and optimal experimental design are particularly challenging. The community has already developed many methods and software packages which aim to facilitate these tasks. However, there is a lack of suitable benchmark problems which allow a fair and systematic evaluation and comparison of these contributions. RESULTS: Here we present BioPreDyn-bench, a set of challenging parameter estimation problems which aspire to serve as reference test cases in this area. This set comprises six problems including medium and large-scale kinetic models of the bacterium E. coli, baker's yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells, and a generic signal transduction network. The level of description includes metabolism, transcription, signal transduction, and development. For each problem we provide (i) a basic description and formulation, (ii) implementations ready-to-run in several formats, (iii) computational results obtained with specific solvers, (iv) a basic analysis and interpretation. CONCLUSIONS: This suite of benchmark problems can be readily used to evaluate and compare parameter estimation methods. Further, it can also be used to build test problems for sensitivity and identifiability analysis, model reduction and optimal experimental design methods. The suite, including codes and documentation, can be freely downloaded from the BioPreDyn-bench website, https://sites.google.com/site/biopredynbenchmarks/ .

A consensus approach for estimating the predictive accuracy of dynamic models in biology.

Mathematical models that predict the complex dynamic behaviour of cellular networks are fundamental in systems biology, and provide an important basis for biomedical and biotechnological applications. However, obtaining reliable predictions from large-scale dynamic models is commonly a challenging task due to lack of identifiability. The present work addresses this challenge by presenting a methodology for obtaining high-confidence predictions from dynamic models using time-series data. First, to preserve the complex behaviour of the network while reducing the number of estimated parameters, model parameters are combined in sets of meta-parameters, which are obtained from correlations between biochemical reaction rates and between concentrations of the chemical species. Next, an ensemble of models with different parameterizations is constructed and calibrated. Finally, the ensemble is used for assessing the reliability of model predictions by defining a measure of convergence of model outputs (consensus) that is used as an indicator of confidence. We report results of computational tests carried out on a metabolic model of Chinese Hamster Ovary (CHO) cells, which are used for recombinant protein production. Using noisy simulated data, we find that the aggregated ensemble predictions are on average more accurate than the predictions of individual ensemble models. Furthermore, ensemble predictions with high consensus are statistically more accurate than ensemble predictions with large variance. The procedure provides quantitative estimates of the confidence in model predictions and enables the analysis of sufficiently complex networks as required for practical applications.

Development of cultivation strategies for friulimicin production in Actinoplanes friuliensis.

Actinoplanes friuliensis is a rare actinomycete which produces the highly potent lipopeptide antibiotic friulimicin. This lipopeptide antibiotic is active against a broad range of multi-resistant gram-positive bacteria such as methicillin-resistant Enterococcus sp. and Staphylococcus aureus (MRE, MRSA) strains. Antibiotic biosynthesis and regulation in actinomycetes is very complex. In order to study the biosynthesis of these species and to develop efficient production processes, standardized cultivation conditions are a prerequisite. For this reason a chemically defined production medium for A. friuliensis was developed. With this chemically defined medium it was possible to analyze the influence of medium components on growth and antibiotic biosynthesis. These findings were used to develop process strategies for friulimicin production. The focus of the project presented here was to develop cultivation strategies which included fed-batch and continuous cultivation processes. In fed-batch processes, volumetric productivities for friulimicin of 1-2 mg/l h were achieved. In a perfusion process, a very simple cell retention system, which works via sedimentation of the mycelial cell pellets, was used. With this system, stable continuous cultivations with cell retention were dependent on the dilution rate. With a dilution rate of 0.05 h(-1), cell retention worked well and volumetric productivity of friulimicin was enhanced to 3-5 mg/l h. With a higher dilution rate of 0.1 h(-1), friulimicin production ceased because cell retention was not possible any longer with this simple cell retention system. In order to support process development, cultivation data were used to characterize metabolic fluxes in the developed friulimicin production processes.

The genome of Xanthomonas campestris pv. campestris B100 and its use for the reconstruction of metabolic pathways involved in xanthan biosynthesis.

The complete genome sequence of the Xanthomonas campestris pv. campestris strain B100 was established. It consisted of a chromosome of 5,079,003bp, with 4471 protein-coding genes and 62 RNA genes. Comparative genomics showed that the genes required for the synthesis of xanthan and xanthan precursors were highly conserved among three sequenced X. campestris pv. campestris genomes, but differed noticeably when compared to the remaining four Xanthomonas genomes available. For the xanthan biosynthesis genes gumB and gumK earlier translational starts were proposed, while gumI and gumL turned out to be unique with no homologues beyond the Xanthomonas genomes sequenced. From the genomic data the biosynthesis pathways for the production of the exopolysaccharide xanthan could be elucidated. The first step of this process is the uptake of sugars serving as carbon and energy sources wherefore genes for 15 carbohydrate import systems could be identified. Metabolic pathways playing a role for xanthan biosynthesis could be deduced from the annotated genome. These reconstructed pathways concerned the storage and metabolization of the imported sugars. The recognized sugar utilization pathways included the Entner-Doudoroff and the pentose phosphate pathway as well as the Embden-Meyerhof pathway (glycolysis). The reconstruction indicated that the nucleotide sugar precursors for xanthan can be converted from intermediates of the pentose phosphate pathway, some of which are also intermediates of glycolysis or the Entner-Doudoroff pathway. Xanthan biosynthesis requires in particular the nucleotide sugars UDP-glucose, UDP-glucuronate, and GDP-mannose, from which xanthan repeat units are built under the control of the gum genes. The updated genome annotation data allowed reconsidering and refining the mechanistic model for xanthan biosynthesis.

A broad diversity of volatile carboxylic acids, released by a bacterial aminoacylase from axilla secretions, as candidate molecules for the determination of human-body odor type.

Human body odor is to a large part determined by secretions of glands in the axillary regions. Two key odoriferous principles, 3-methylhex-2-enoic acid (3MH2; 4/5) and 3-hydroxy-3-methylhexanoic acid (HMHA; 6) have been shown to be released from glutamine conjugates secreted in the axilla by a specific N(alpha)-acyl-glutamine aminoacylase (N-AGA) obtained from axilla isolates of Corynebacteria sp. However, the low number of different odorants reported in humans stands in contrast to the observed high inter-individual variability in body odors. Axilla secretions of individual donors were, therefore, analyzed in detail. The secretions were treated with N-AGA, analyzed by GC/MS, and compared to undigested controls. Over 28 different carboxylic acids were released by this enzyme from odorless axilla secretions (Table 1). Many of these body odorants have not been reported before from a natural source, and they include several aliphatic 3-hydroxy acids with 4-Me branches, 3,4-unsaturated, 4-Et-branched aliphatic acids, and a variety of degradation products of amino acids. The odor threshold of some of the acids was found to be in the range of 1 ng. Most of these compounds were present in all donors tested, but in highly variable relative amounts, and they are, thus, candidate molecules as key components of a 'compound odor' determining the individual types of human body odor.

Model-based inference of gene expression dynamics from sequence information.

A dynamic model of prokaryotic gene expression is developed that makes considerable use of gene sequence information. The main contribution arises from the fact that the combined gene expression model allows us to access the impact of altering a nucleotide sequence on the dynamics of gene expression rates mechanistically. The high level of detail of the mathematical model is considered as an important step towards bringing together the tremendous amount of biological in-depth knowledge that has been accumulated at the molecular level, using a systems level analysis (in the sense of a bottom-up, inductive approach). This enables to the model to provide highly detailed insights into the various steps of the protein expression process and it allows us to access possible targets for model-based design. Taken as a whole, the mathematical gene expression model presented in this study provides a comprehensive framework for a thorough analysis of sequence-related effects on the stages of mRNA synthesis, mRNA degradation and ribosomal translation, as well as their nonlinear interconnectedness. Therefore, it may be useful in the rational design of recombinant bacterial protein synthesis systems, the modulation of enzyme activities in pathway design, in vitro protein biosynthesis, and RNA-based vaccination.

Model of central and trimethylammonium metabolism for optimizing L-carnitine production by E. coli.

The application of metabolic engineering principles to the rational design of microbial production processes crucially depends on the ability to make quantitative descriptions of the systemic ability of the central carbon metabolism to redirect fluxes to the product-forming pathways. The aim of this work was to further our understanding of the steps controlling the biotransformation of trimethylammonium compounds into L-carnitine by Escherichia coli. Despite the importance of L-carnitine production processes, development of a model of the central carbon metabolism linked to the secondary carnitine metabolism of E. coli has been severely hampered by the lack of stoichiometric information on the metabolic reactions taking place in the carnitine metabolism. Here we present the design and experimental validation of a model which, for the first time, links the carnitine metabolism with the reactions of glycolysis, the tricarboxylic acid cycle and the pentose-phosphate pathway. The results demonstrate a need for a high production rate of ATP to be devoted to the biotransformation process. The results demonstrate that ATP is used up in a futile cycle, since both trimethylammonium compound carriers CaiT and ProU operate simultaneously. To improve the biotransformation process, resting processes as well as CaiT or ProU knock out mutants would yield a more efficient system for producing L-carnitine from crotonobetaine or D-carnitine.

Metabolic design based on a coupled gene expression-metabolic network model of tryptophan production in Escherichia coli.

The presumably high potential of a holistic design approach for complex biochemical reaction networks is exemplified here for the network of tryptophan biosynthesis from glucose, a system whose components have been investigated thoroughly before. A dynamic model that combines the behavior of the trp operon gene expression with the metabolic network of central carbon metabolism and tryptophan biosynthesis is investigated. This model is analyzed in terms of metabolic fluxes, metabolic control, and nonlinear optimization. We compare two models for a wild-type strain and another model for a tryptophan producer. An integrated optimization of the whole network leads to a significant increase in tryptophan production rate for all systems under study. This enhancement is well above the increase that can be achieved by an optimization of subsystems. A constant ratio of control coefficients on tryptophan synthesis rate has been identified for the models regarding or disregarding trp operon expression. Although we found some examples where flux control coefficients even contradict the trends of enzyme activity changes in an optimized profile, flux control can be used as an indication for enzymes that have to be taken into account in optimization.

Optimal re-design of primary metabolism in Escherichia coli using linlog kinetics.

This paper examines the validity of the linlog approach, which was recently developed in our laboratory, by comparison of two different kinetic models for the metabolic network of Escherichia coli. The first model is a complete mechanistic model; the second is an approximative model in which linlog kinetics are applied. The parameters of the linlog model (elasticities) are derived from the mechanistic model. Three different optimization cases are examined. In all cases, the objective is to calculate the enzyme levels that maximize a certain flux while keeping the total amount of enzyme constant and preventing large changes of metabolite concentrations. For an average variation of metabolite levels of 10% and individual changes of a factor 2, the predicted enzyme levels, metabolite concentrations and fluxes of both models are highly similar. This similarity holds for changes in enzyme level of a factor 4-6 and for changes in fluxes up to a factor 6. In all three cases, the predicted optimal enzyme levels could neither have been found by intuition-based approaches, nor on basis of flux control coefficients. This demonstrates that kinetic models are essential tools in Metabolic Engineering. In this respect, the linlog approach is a valuable extension of MCA, since it allows construction of kinetic models, based on MCA parameters, that can be used for constrained optimization problems and are valid for large changes of metabolite and enzyme levels.

Identification of odoriferous sulfanylalkanols in human axilla secretions and their formation through cleavage of cysteine precursors by a C-S lyase isolated from axilla bacteria.

Human axillary odor is known to be formed upon the action of Corynebacteria sp. on per se odorless axilla secretions. Besides the known odoriferous acids, we report the occurrence in human axilla secretions of four odoriferous sulfanylalkanols, namely 3-sulfanylhexan-1-ol (3), 2-methyl-3-sulfanylbutan-1-ol (4), 3-sulfanylpentan-1-ol (5), and 3-methyl-3-sulfanylhexan-1-ol (6). These compounds have a pungent sweat/kitchen odor, also reminiscent of onions with some fruity connotations, and perception thresholds in the pg/l range. It was postulated that the odorless precursors for these compounds are cysteine conjugates. Bacterial isolates obtained from the human axilla and belonging to the Corynebacteria were, indeed, found to have the enzymatic capacity to release various thiols from cysteine conjugates. The metC gene, which is known to code for a cystathione-beta-lyase, was cloned from the axilla isolate Corynebacterium striatum Ax20 and heterologously expressed in E. coli. The pure recombinant enzyme cleaves various cysteine conjugates and has a similar substrate specificity as the cell homogenates of the wild-type. The recombinant enzyme was finally incubated with odorless axilla secretions and shown to release odoriferous thiols.

A specific bacterial aminoacylase cleaves odorant precursors secreted in the human axilla.

Human axillary odor is known to be formed upon the action of Corynebacteria sp. on odorless axilla secretions. The known axilla odor determinant 3-methyl-2-hexenoic acid was identified in hydrolyzed axilla secretions along with a chemically related compound, 3-hydroxy-3-methylhexanoic acid. The natural precursors of both these acids were purified from non-hydrolyzed axilla secretions. From liquid chromatography/mass spectrometry analysis, it appeared that the acids are covalently linked to a glutamine residue in fresh axilla secretions, and the corresponding conjugates were synthesized for confirmation. Bacterial isolates obtained from the human axilla and belonging to the Corynebacteria were found to release the acids from these odorless precursors in vitro. A Zn(2+)-dependent aminoacylase mediating this cleavage was purified from Corynebacterium striatum Ax20, and the corresponding gene agaA was cloned and heterologously expressed in Escherichia coli. The enzyme is highly specific for the glutamine residue but has a low specificity for the acyl part of the substrate. agaA is closely related to many genes coding for enzymes involved in the cleavage of N-terminal acyl and aryl substituents from amino acids. This is the first report of the structure elucidation of precursors for human body odorants and the isolation of the bacterial enzyme involved in their cleavage.

Machine scoring of Her2/neu immunohistochemical stains.

OBJECTIVE: To establish the feasibility of a machine scoring method for her2/neu immunohistochemistry in samples of breast carcinoma. STUDY DESIGN: A total of 65 consecutive cases of breast carcinoma with immunohistochemical stainingfor her2/neu by the Herceptest (Dako Corp., Carpinteria, California, U.S.A.) method (DAB chromogen with hematoxylin counterstain) were analyzed using an Extended Slide Wizard (Tripath Imaging, Inc., Burlington, North Carolina, U.S.A.) workstation running prototype software. Representative fields of view from the positive control, negative control and up to 10 fields from the stained tumor sample were captured interactively with a phased alternating line 3 CCD color camera. To determine the amount of specific membrane staining, chromogen separation of nuclear counterstain and membrane-positive stain was performed based on their respective absorption coefficients in the three color channels. The amount of specific membrane staining was scored based on a training set covering the rangefrom 0 to 3 + staining scores according to Dako. Manual scores of 2 + were tested for amplification by fluorescence in situ hybridization. RESULTS: The automated scoring results correlated highly with the manual scores obtained per the Herceptest (Dako) instructions (R2>.92). The results were obtained in real time in the interactive mode. CONCLUSION: Machine scoring of immunohistochemical stains is practical, rapid and inherently reproducible, especially for samples with 1+ and 2+ manual scores.

Dynamic modeling of the central carbon metabolism of Escherichia coli.

Application of metabolic engineering principles to the rational design of microbial production processes crucially depends on the ability to describe quantitatively the systemic behavior of the central carbon metabolism to redirect carbon fluxes to the product-forming pathways. Despite the importance for several production processes, development of an essential dynamic model for central carbon metabolism of Escherichia coli has been severely hampered by the current lack of kinetic information on the dynamics of the metabolic reactions. Here we present the design and experimental validation of such a dynamic model, which, for the first time, links the sugar transport system (i.e., phosphotransferase system [PTS]) with the reactions of glycolysis and the pentose-phosphate pathway. Experimental observations of intracellular concentrations of metabolites and cometabolites at transient conditions are used to validate the structure of the model and to estimate the kinetic parameters. Further analysis of the detailed characteristics of the system offers the possibility of studying important questions regarding the stability and control of metabolic fluxes.