A novel extraction protocol is described with which metabolites, proteins and RNA are sequentially extracted from the same sample, thereby providing a convenient procedure for the analysis of replicates as well as exploiting the inherent biological variation of independent samples for multivariate data analysis. A detection of 652 metabolites, 297 proteins and clear RNA bands in a single Arabidopsis thaliana leaf sample was validated by analysis with gas chromatography coupled to a time of flight mass spectrometer for metabolites, two-dimensional liquid chromatography coupled to mass spectrometry for proteins, and Northern blot analysis for RNA. A subset of the most abundant proteins and metabolites from replicate analysis of different Arabidopsis accessions was merged to form an integrative dataset allowing both classification of different genotypes and the unbiased analysis of the hierarchical organization of proteins and metabolites within a real biochemical network.

Current efforts aim to functionally characterize each gene in model plants. Frequently, however, no morphological or biochemical phenotype can be ascribed for antisense or knock-out plant genotypes. This is especially the case when gene suppression or knockout is targeted to isoenzymes or gene families. Consequently, pleiotropic effects and gene redundancy are responsible for phenotype resistance. Here, techniques are presented to detect unexpected pleiotropic changes in such instances despite very subtle changes in overall metabolism. The method consists of the relative quantitation of >1,000 compounds by GC͞time-of-flight MS, followed by classical statistics and multivariate clustering. Complementary to these tools, metabolic networks are constructed from pair-wise analysis of linear metabolic correlations. The topology of such networks reflects the underlying regulatory pathway structure. A differential analysis of network connectivity was applied for a silent potato plant line suppressed in expression of sucrose synthase isoform II. Metabolic alterations could be assigned to carbohydrate and amino acid metabolism even if no difference in average metabolite levels was found.metabolomics ͉ metabonomics ͉ data mining ͉ regulatory networks ͉ functional genomics S ilent phenotypes are genetically modified organisms that do not show obvious changes in morphology, yield, growth rates, or related parameters when compared with parental lines under given physiological conditions (1). This phenomenon is especially astonishing when genes are altered that are known to play pivotal roles in overall plant fitness (2). It is thought that such organisms might have found ways to circumvent the deleterious effects of the mutated genes or that redundancy in gene families (3) could prevent injurious outcomes. The most apparent form of gene redundancy is the frequent coexpression of enzyme isoforms involved in various metabolic pathways (4-6). In most cases, enzyme isoforms cannot be distinguished on the basis of enzyme activities. Here, techniques like metabolomics might aid functional characterization (7), assuming that the primary alteration of enzyme-encoding genes pleiotropically affects biochemical pathways. The working hypothesis is that a network of metabolic associations represents a snapshot response of the underlying biochemical network at a given biological situation, which then can be used to observe changes between different genotypes (8, 9). This view is theoretically supported by the concept of ''metabolic control analysis'' (10) and the concept of maximal connectivity in a biochemical network (11). Specifically, the effects on metabolite pool concentrations may be higher than the alteration in enzymatic flux control or enzyme activities. Recently, silent yeast phenotypes were discriminated from WT strains by using multivariate statistics applied to NMR (12) or MS (13) based metabolic fingerprints, with the objective to cluster genotypes together that were defective in genes with similar functions. However, resolu...

Transient expression systems allow the rapid production of recombinant proteins in plants. Such systems can be scaled up to several hundred kilograms of biomass, making them suitable for the production of pharmaceutical proteins required at short notice, such as emergency vaccines. However, large‐scale transient expression requires the production of recombinant Agrobacterium tumefaciens strains with the capacity for efficient gene transfer to plant cells. The complex media often used for the cultivation of this species typically include animal‐derived ingredients that can contain human pathogens, thus conflicting with the requirements of good manufacturing practice (GMP). We replaced all the animal‐derived components in yeast extract broth (YEB) cultivation medium with soybean peptone, and then used a design‐of‐experiments approach to optimize the medium composition, increasing the biomass yield while maintaining high levels of transient expression in subsequent infiltration experiments. The resulting plant peptone Agrobacterium medium (PAM) achieved a two‐fold increase in OD600 compared to YEB medium during a 4‐L batch fermentation lasting 18 h. Furthermore, the yields of the monoclonal antibody 2G12 and the fluorescent protein DsRed were maintained when the cells were cultivated in PAM rather than YEB. We have thus demonstrated a simple, efficient and scalable method for medium optimization that reduces process time and costs. The final optimized medium for the cultivation of A. tumefaciens completely lacks animal‐derived components, thus facilitating the GMP‐compliant large‐scale transient expression of recombinant proteins in plants.

Protein accumulation is the hallmark of various neuronal, muscular, and other human disorders. It is also often seen in the liver as a major protein‐secretory organ. For example, aggregation of mutated alpha1‐antitrypsin (AAT), referred to as PiZ, is a characteristic feature of AAT deficiency, whereas retention of hepatitis B surface protein (HBs) is found in chronic hepatitis B (CHB) infection. We investigated the interaction of both proteotoxic stresses in humans and mice. Animals overexpressing both PiZ and HBs (HBs‐PiZ mice) had greater liver injury, steatosis, and fibrosis. Later they exhibited higher hepatocellular carcinoma load and a more aggressive tumor subtype. Although PiZ and HBs displayed differing solubility properties and distinct distribution patterns, HBs‐PiZ animals manifested retention of AAT/HBs in the degradatory pathway and a marked accumulation of the autophagy adaptor p62. Isolation of p62‐containing particles revealed retained HBs/AAT and the lipophagy adapter perilipin‐2. p62 build‐up led to activation of the p62–Nrf2 axis and emergence of reactive oxygen species. Our results demonstrate that the simultaneous presence of two prevalent proteotoxic stresses promotes the development of liver injury due to protein retention and activation of the p62–Nrf2 axis. In humans, the PiZ variant was over‐represented in CHB patients with advanced liver fibrosis (unadjusted odds ratio = 9.92 [1.15–85.39]). Current siRNA approaches targeting HBs/AAT should be considered for these individuals. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.