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PubMed2004

Changes in the mitochondrial proteome during the anoxia to air transition in rice focus around cytochrome-containing respiratory complexes.

The ability of rice seedlings to grow from dry seed under anoxia provides a rare opportunity in a multicellular eukaryote to study the stages of mitochondrial biogenesis triggered by oxygen availability. The function and proteome of rice mitochondria synthesized under 6 days of anoxia following 1 day of air adaptation have been compared with mitochondria isolated from 7-day aerobically grown rice seedlings. Rice coleoptiles grown under anoxia, and the mitochondria isolated from them respired very slowly compared with air-adapted and air-grown seedlings. Immunodetection of key mitochondrial protein markers, isoelectric focusing electrophoresis followed by SDS-PAGE to make soluble mitochondria proteome maps, and shotgun sequencing of mitochondrial proteins by liquid chromatography-tandem mass spectrometry all revealed similar patterns of the major function categories of mitochondrial proteins from both anoxic and air-adapted samples. Activity analysis showed respiratory oxidases markedly increased in activity during the air adaptation of seedlings. Blue-native electrophoresis followed by SDS-PAGE of mitochondrial membrane proteins clearly showed the very low abundance of assembled b/c complex and cytochrome c(1) oxidase complex in the mitochondrial membrane in anoxic samples and the dramatic increase in the abundance of these complexes on air adaptation. Total heme content, cytochrome absorbance spectra, and the electron carrier, cytochrome c, also increased markedly on air adaptation. These results likely reflect limited heme synthesis for cytochrome assembly in the absence of oxygen and represent a discrete and reversible blockage of full mitochondrial biogenesis in this anoxia-tolerant species.

Air↗

PubMed2001

Proteomic profiling from human samples: the body fluid alternative.

Proteomics is one of the technologies rapidly changing our approach to drug development. The applications of proteomics, particularly with reference to analysis of body fluid samples, will be described. Proteomic analysis involves the systematic separation, identification and characterisation of proteins present in a biological sample. By comparing the proteins present in diseased samples with those present in normal samples, it is possible to identify changes in expression of proteins that potentially may be related to organ toxicity. Proteomics is regarded as a sister technology to genomics. Although the pattern of gene activity will be abnormal in a tissue with a pathological lesion, there can be a poor correlation between the level of activity of different genes and the relative abundance within the tissue of the corresponding proteins. This is especially true where the mode of action of the test material interferes with protein synthesis and/or post translational modification. Consequently, the information about a pathological process that can be derived at the level of gene activity is incomplete. Proteomics has now made it possible to analyse proteins using high throughput, automated techniques. Although both mRNA and proteomic profiling can be applied to tissue samples, analysis of body fluids (e.g. serum, urine, CSF, synovial fluid) is restricted to proteomics. In these cases the protein composition is derived from many tissues and processes. Proteomic analysis can yield information on disease processes and potential response to treatment. Examples will be presented of the identification of surrogate markers for hepatocellular carcinoma, breast cancer, from cerebrospinal fluid in humans and gentamicin toxicity in the rat.

Body Fluids↗

PubMed2004

The application of mass spectrometry to identify immunogenic components of excretory/secretory products from adult Dictyocaulus viviparus.

Proteomics has come to the forefront in the post-genomic era. The ability to compare and identify proteins expressed in a particular cell type under specific physiological or pathological states requires a range of technologies, including separation of complex protein or peptide mixtures, densitometry-based or isotope-coded methods for comparison of multiple proteomes, and mass spectrometric methods for identification of individual low abundance proteins. Although an emergent technology, thus far, proteomics has provided new perspectives on many problems in biomedical science. In parasitology, proteomics has been used to answer specific biological questions relating to survival and development, and also to identify candidates for vaccines. Here, we describe an ongoing research programme in which proteomics is being used to identify potential vaccine candidates for the bovine lungworm, Dictyocaulus viviparus. This work is focusing on antibody responses to the adult parasite excretory/secretory (ES) products, with selection of candidate antigens based on differential screening with serum from immune versus non-immune animals to simplify the proteome and the ensuing analytical challenges. Thus far, we have identified seven candidate proteins using this strategy. Of these, one protein showed significant identity to a previously cloned gene from D. viviparus, whilst the other six proteins have shown no significant identities. Isolation of further peptide sequences is now warranted to facilitate cloning of the genes encoding these antigens.

Amino Acid Sequence↗

PubMed2004

In vitro biomarker discovery for atherosclerosis by proteomics.

The purpose of this study was to identify in vitro and then prioritize a tractable set of protein biomarker candidates of atherosclerosis that may eventually be developed to measure the extent, progression, regression, and stability of atherosclerotic lesions. A study was conducted using an in vitro"foam cell" model based on the stimulation of differentiated THP1 cells with oxidized low-density lipoprotein (oxidized LDL) as compared with low-density lipoprotein (LDL). Analysis of the proteins contained in the cell supernatant using proteome scanning technology identified 59 proteins as being increased, 57 with no statistically measurable difference, and 17 decreasing in abundance following treatment with oxidized LDL, as compared with LDL. From the up-regulated list, proteins were prioritized based on their analytical confidence as well as their relevance to atherosclerosis pathways. Within the group of increased abundance, seven families of proteins were of particular interest: fatty acid-binding proteins, chitinase-like enzymes, cyclophilins, cathepsins, proteoglycans, urokinase-type plasminogen activator receptor, and a macrophage scavenger receptor.

Amino Acid Sequence↗

PubMed2006

Differential expression analysis of Escherichia coli proteins using a novel software for relative quantitation of LC-MS/MS data.

The study of changes in protein levels between samples derived from cells representing different biological conditions is a key to the understanding of cellular function. There are two main methods available that allow both for global scanning for significantly varying proteins and targeted profiling of proteins of interest. One method is based on 2-D gel electrophoresis and image analysis of labelled proteins. The other method is based on LC-MS/MS analysis of either unlabelled peptides or peptides derived from isotopically labelled proteins or peptides. In this study, the non-labelling approach was used involving a new software, DeCyder MS Differential Analysis Software (DeCyder MS) intended for automated detection and relative quantitation of unlabelled peptides in LC-MS/MS data. Total protein extracts of E. coli strains expressing varying levels of dihydrofolate reductase and integron integrase were digested with trypsin and analyzed using a nanoscale liquid chromatography system, Ettan MDLC, online connected to an LTQTM linear ion-trap mass spectrometer fitted with a nanospray interface. Acquired MS data were subjected to DeCyder MS analysis where 2-D representations of the peptide patterns from individual LC-MS/MS analyses were matched and compared. This approach to unlabelled quantitative analysis of the E. coli proteome resulted in relative protein abundances that were in good agreement with results obtained from traditional methods for measuring protein levels.

Amino Acid Sequence↗

PubMed2024

Specificity profiling of deubiquitylases against endogenously generated ubiquitin-protein conjugates.

Deubiquitylating enzymes (DUBs) remove ubiquitin from proteins thereby regulating their stability or activity. Our understanding of DUB-substrate specificity is limited because DUBs are typically not compared to each other against many physiological substrates. By broadly inhibiting DUBs in Xenopus egg extract, we generated hundreds of ubiquitylated proteins and compared the ability of 30 DUBs to deubiquitylate them using quantitative proteomics. We identified five high-impact DUBs (USP7, USP9X, USP36, USP15, and USP24) that each reduced ubiquitylation of over 10% of the isolated proteins. Candidate substrates of high-impact DUBs showed substantial overlap and were enriched for disordered regions, suggesting this feature may promote substrate recognition. Other DUBs showed lower impact and non-overlapping specificity, targeting distinct non-disordered proteins including complexes such as the ribosome or the proteasome. Altogether our study identifies candidate DUB substrates and defines patterns of functional redundancy and specificity, revealing substrate characteristics that may influence DUB-substrate recognition.

Substrate Specificity↗

PubMedDate not supplied

Primordial proteins and HIV.

Primordial proteins regulate the response of nanobacteria to variations in their environment and reinforce existing pathogenic potentials. By analyzing specific response patterns, we predicted the prevalence of nanobacteria in HIV--and in the atmosphere. A current clinical study indicates the identification of a possibly giant nanobacterial reservoir in Africa: a significant fraction of a test group (40 HIV-infected mothers and 13 babies) was infected with nanobacteria. Concurrently, a multitude of 80-300 nm nanovesicles, apparently nanobacteria, were detected in the atmosphere of the Earth. Nanobacterial infections in HIV are possibly comparable to the twin epidemics HIV and tuberculosis. Models inspired by proteomics recommend methods to inactivate nanobacteria (and other slime-producing bacteria) in the body.

Animals↗

PubMed2025

Longitudinal multi-omics in alpha-synuclein Drosophila model discriminates disease- from age-associated pathologies in Parkinson's disease.

Parkinson's disease (PD) starts decades before symptoms appear, usually in the later decades of life, when age-related changes are occurring. To identify molecular changes early in the disease course and distinguish PD pathologies from aging, we generated Drosophila expressing alpha-synuclein (αSyn) in neurons and performed longitudinal bulk transcriptomics and proteomics on brains at six time points across the lifespan and compared the data to healthy control flies as well as human post-mortem brain datasets. We found that translational and energy metabolism pathways were downregulated in αSyn flies at the earliest timepoints; comparison with the aged control flies suggests that elevated αSyn accelerates changes associated with normal aging. Unexpectedly, single-cell analysis at a mid-disease stage revealed that neurons upregulate protein synthesis and nonsense-mediated decay, while glia drive their overall downregulation. Longitudinal multi-omics approaches in animal models can thus help elucidate the molecular cascades underlying neurodegeneration vs. aging and co-pathologies.

Journal Article↗

PubMed2005

Inparanoid: a comprehensive database of eukaryotic orthologs.

The Inparanoid eukaryotic ortholog database (http://inparanoid.cgb.ki.se/) is a collection of pairwise ortholog groups between 17 whole genomes; Anopheles gambiae, Caenorhabditis briggsae, Caenorhabditis elegans, Drosophila melanogaster, Danio rerio, Takifugu rubripes, Gallus gallus, Homo sapiens, Mus musculus, Pan troglodytes, Rattus norvegicus, Oryza sativa, Plasmodium falciparum, Arabidopsis thaliana, Escherichia coli, Saccharomyces cerevisiae and Schizosaccharomyces pombe. Complete proteomes for these genomes were derived from Ensembl and UniProt and compared pairwise using Blast, followed by a clustering step using the Inparanoid program. An Inparanoid cluster is seeded by a reciprocally best-matching ortholog pair, around which inparalogs (should they exist) are gathered independently, while outparalogs are excluded. The ortholog clusters can be searched on the website using Ensembl gene/protein or UniProt identifiers, annotation text or by Blast alignment against our protein datasets. The entire dataset can be downloaded, as can the Inparanoid program itself.

Animals↗

PubMed2005

Bioinformatics in microbial biotechnology--a mini review.

The revolutionary growth in the computation speed and memory storage capability has fueled a new era in the analysis of biological data. Hundreds of microbial genomes and many eukaryotic genomes including a cleaner draft of human genome have been sequenced raising the expectation of better control of microorganisms. The goals are as lofty as the development of rational drugs and antimicrobial agents, development of new enhanced bacterial strains for bioremediation and pollution control, development of better and easy to administer vaccines, the development of protein biomarkers for various bacterial diseases, and better understanding of host-bacteria interaction to prevent bacterial infections. In the last decade the development of many new bioinformatics techniques and integrated databases has facilitated the realization of these goals. Current research in bioinformatics can be classified into: (i) genomics--sequencing and comparative study of genomes to identify gene and genome functionality, (ii) proteomics--identification and characterization of protein related properties and reconstruction of metabolic and regulatory pathways, (iii) cell visualization and simulation to study and model cell behavior, and (iv) application to the development of drugs and anti-microbial agents. In this article, we will focus on the techniques and their limitations in genomics and proteomics. Bioinformatics research can be classified under three major approaches: (1) analysis based upon the available experimental wet-lab data, (2) the use of mathematical modeling to derive new information, and (3) an integrated approach that integrates search techniques with mathematical modeling. The major impact of bioinformatics research has been to automate the genome sequencing, automated development of integrated genomics and proteomics databases, automated genome comparisons to identify the genome function, automated derivation of metabolic pathways, gene expression analysis to derive regulatory pathways, the development of statistical techniques, clustering techniques and data mining techniques to derive protein-protein and protein-DNA interactions, and modeling of 3D structure of proteins and 3D docking between proteins and biochemicals for rational drug design, difference analysis between pathogenic and non-pathogenic strains to identify candidate genes for vaccines and anti-microbial agents, and the whole genome comparison to understand the microbial evolution. The development of bioinformatics techniques has enhanced the pace of biological discovery by automated analysis of large number of microbial genomes. We are on the verge of using all this knowledge to understand cellular mechanisms at the systemic level. The developed bioinformatics techniques have potential to facilitate (i) the discovery of causes of diseases, (ii) vaccine and rational drug design, and (iii) improved cost effective agents for bioremediation by pruning out the dead ends. Despite the fast paced global effort, the current analysis is limited by the lack of available gene-functionality from the wet-lab data, the lack of computer algorithms to explore vast amount of data with unknown functionality, limited availability of protein-protein and protein-DNA interactions, and the lack of knowledge of temporal and transient behavior of genes and pathways.

Journal Article↗

PubMed2004

[The tortuose path of human evolution].

The human genome sequencing and also the chimpanzee's, among others alive beings in every kingdom, and the similarities between genomes, due to an unique life origin, has developed two movements in the Biological Sciences to the XXI Century. In the first place to find a genetic explanation to understand the genomic affinity, very narrow in many cases, in front of the reality, with abyssal differences in behavior, which undervalue the significance of the genomic resemblance between the alive beings. The second movement is directed to ethological studies of the animal behavior and conduct, as a real fact. Special interest has the comparative studies since the two points of view, the genome and proteome in one side and ethology in front, both related to the Homo sapiens sapiens and his relatives, the great anthropomorphic apes, and consequently beside the names of Craig Venter, Collins and collaborators, artificers of the human genome sequencing, appear, unde revaluation, those of Leakey, Goodall, Fossey and Galdikas, specialists in anthropology and ethology of chimpanzees, gorillas and orangutans. These ideas are complementary in order to a better understanding of the origin, human evolution and behavior, shedding light on human cognitive abilities.

Animals↗

PubMed2006

Proteome comparison following self- and across-pollination in self-incompatible apricot (Prunus armeniaca L.).

The study compared the protein differences between self- and across-pollinated self-incompatible (SI) apricots by two-dimensional gel electrophoresis and liquid chromatography-electrospray ion trap tandem mass spectrometry, the results showed that nine protein spots were expressed in self-pollinated pistil and only one was expressed in cross-pollinated pistils. Sixteen and three protein spots were up- and down-regulated in cross-pollinated pistils, respectively, compared with self-pollinated pistils. Seven protein spots were identified unambiguously by SEQUEST in NCBI protein database: Actin-12, enolase, MYB transcription-factor-like protein, heat-shock protein 70 were upregulated in cross-pollinated pistils compared with self-pollinated pistils; and actin-7, actin-8 and fructose bisphosphate aldolase-like protein were detected only in self-pollinated pistils.

Amino Acid Sequence↗

PubMedDate not supplied

Development and evaluation of a micro- and nanoscale proteomic sample preparation method.

Challenges associated with the efficient and effective preparation of micro- and nanoscale (micro- and nanogram) clinical specimens for proteomic applications include the unmitigated sample losses that occur during the processing steps. Herein, we describe a simple "single-tube" preparation protocol appropriate for small proteomic samples using the organic cosolvent, trifluoroethanol (TFE) that circumvents the loss of sample by facilitating both protein extraction and protein denaturation without requiring a separate cleanup step. The performance of the TFE-based method was initially evaluated by comparisons to traditional detergent-based methods on relatively large scale sample processing using human breast cancer cells and mouse brain tissue. The results demonstrated that the TFE-based protocol provided comparable results to the traditional detergent-based protocols for larger, conventionally sized proteomic samples (>100 microg protein content), based on both sample recovery and numbers of peptide/protein identifications. The effectiveness of this protocol for micro- and nanoscale sample processing was then evaluated for the extraction of proteins/peptides and shown effective for small mouse brain tissue samples (approximately 30 microg total protein content) and also for samples of approximately 5000 MCF-7 human breast cancer cells (approximately 500 ng total protein content), where the detergent-based methods were ineffective due to losses during cleanup and transfer steps.

Animals↗

PubMed2006

Proteomic analysis of seed dormancy in Arabidopsis.

The mechanisms controlling seed dormancy in Arabidopsis (Arabidopsis thaliana) have been characterized by proteomics using the dormant (D) accession Cvi originating from the Cape Verde Islands. Comparative studies carried out with freshly harvested dormant and after-ripened non-dormant (ND) seeds revealed a specific differential accumulation of 32 proteins. The data suggested that proteins associated with metabolic functions potentially involved in germination can accumulate during after-ripening in the dry state leading to dormancy release. Exogenous application of abscisic acid (ABA) to ND seeds strongly impeded their germination, which physiologically mimicked the behavior of D imbibed seeds. This application resulted in an alteration of the accumulation pattern of 71 proteins. There was a strong down-accumulation of a major part (90%) of these proteins, which were involved mainly in energetic and protein metabolisms. This feature suggested that exogenous ABA triggers proteolytic mechanisms in imbibed seeds. An analysis of de novo protein synthesis by two-dimensional gel electrophoresis in the presence of [(35)S]-methionine disclosed that exogenous ABA does not impede protein biosynthesis during imbibition. Furthermore, imbibed D seeds proved competent for de novo protein synthesis, demonstrating that impediment of protein translation was not the cause of the observed block of seed germination. However, the two-dimensional protein profiles were markedly different from those obtained with the ND seeds imbibed in ABA. Altogether, the data showed that the mechanisms blocking germination of the ND seeds by ABA application are different from those preventing germination of the D seeds imbibed in basal medium.

Abscisic Acid↗

PubMed2024

Retinal Proteome Profiling of Inherited Retinal Degeneration Across Three Different Mouse Models Suggests Common Drug Targets in Retinitis Pigmentosa.

Inherited retinal degenerations (IRDs) are a leading cause of blindness among the population of young people in the developed world. Approximately half of IRDs initially manifest as gradual loss of night vision and visual fields, characteristic of retinitis pigmentosa (RP). Due to challenges in genetic testing, and the large heterogeneity of mutations underlying RP, targeted gene therapies are an impractical largescale solution in the foreseeable future. For this reason, identifying key pathophysiological pathways in IRDs that could be targets for mutation-agnostic and disease-modifying therapies (DMTs) is warranted. In this study, we investigated the retinal proteome of three distinct IRD mouse models, in comparison to sex- and age-matched wild-type mice. Specifically, we used the Pde6βRd10 (rd10) and RhoP23H/WT (P23H) mouse models of autosomal recessive and autosomal dominant RP, respectively, as well as the Rpe65-/- mouse model of Leber's congenital amaurosis type 2 (LCA2). The mice were housed at two distinct institutions and analyzed using LC-MS in three separate facilities/instruments following data-dependent and data-independent acquisition modes. This cross-institutional and multi-methodological approach signifies the reliability and reproducibility of the results. The large-scale profiling of the retinal proteome, coupled with in vivo electroretinography recordings, provided us with a reliable basis for comparing the disease phenotypes and severity. Despite evident inflammation, cellular stress, and downscaled phototransduction observed consistently across all three models, the underlying pathologies of RP and LCA2 displayed many differences, sharing only four general KEGG pathways. The opposite is true for the two RP models in which we identify remarkable convergence in proteomic phenotype even though the mechanism of primary rod death in rd10 and P23H mice is different. Our data highlights the cAMP and cGMP second-messenger signaling pathways as potential targets for therapeutic intervention. The proteomic data is curated and made publicly available, facilitating the discovery of universal therapeutic targets for RP.

Animals↗

PubMed2025

Dissecting metabolic dysfunction- and alcohol-associated liver disease (MetALD) using proteomic and metabolomic profiles.

BACKGROUND & AIMS: Metabolic dysfunction- and alcohol-associated liver disease (MetALD) is a poorly understood condition that bridges cardiometabolic and alcohol-related pathological characteristics. We aimed to differentiate patients with MetALD whose molecular signatures more closely resemble either alcohol-related liver disease (ALD) or metabolic dysfunction-associated steatotic liver disease (MASLD), and to assess their relative risks of complications and mortality. METHODS: We analysed data from 443,453 European participants in the UK Biobank, including 34,147 with MetALD, 11,220 with ALD, and 124,034 with MASLD. Elastic net regression was used to classify ALD and MASLD based on 249 plasma metabolites and/or 2,941 plasma proteins, with multiple sensitivity analyses. We then applied the resulting concise model to patients with MetALD to identify an alcohol-predominant group (classified as ALD) and a cardiometabolic-predominant group (classified as MASLD). Finally, we evaluated their 15-year risk of major outcomes (heart failure, myocardial infarction, stroke, cirrhosis, hepatocellular carcinoma, and mortality) using Cox regression. RESULTS: The metabolome alone discriminated ALD from MASLD with an AUC of 0.86, while the proteome alone achieved an AUC of 0.96. Adding age, sex, BMI, liver enzymes, or metabolome information did not enhance the AUC of the proteome model. A 10-protein model differentiated ALD from MASLD with an AUC of 0.93. This model identified that patients with alcohol-predominant MetALD had significantly higher risks of mortality, and cirrhosis, along with elevated fibrosis scores and higher fibrosis stages, compared to patients with cardiometabolic-predominant MetALD. CONCLUSIONS: This study highlights the value of proteomic subtyping in MetALD, enabling more personalized treatment strategies and improved prognostic assessment. IMPACT AND IMPLICATIONS: This study underscores the critical importance of distinguishing subtypes of metabolic dysfunction- and alcohol-associated liver disease (MetALD) using proteomic data, providing a foundation for personalized treatment strategies. The findings hold significant relevance for healthcare providers, researchers, and policymakers by highlighting the differing risks associated with alcohol-predominant vs. cardiometabolic-predominant MetALD. Clinicians can apply the classification model developed in this study to more accurately assess patients and guide targeted therapies and preventive measures based on individual profiles. However, limitations of the study, such as reliance on self-reported alcohol consumption and the specificity of diagnostic criteria, necessitate further validation in diverse cohorts.

Humans↗

PubMed2006

Shotgun proteomics for the characterization of subunit composition of mitochondrial complex I.

Here we propose shotgun proteomics as an alternative method to gel-based bottom-up proteomic platform for the structural characterization of mitochondrial NADH:ubiquinone oxidoreductase (complex I). The approach is based on simultaneous identification of subunits after global digestion of the intact complex. Resulting mixture of tryptic peptides is purified, concentrated, separated and online analyzed using nano-scale reverse-phase nano-ESI-MS/MS in a single information dependent acquisition mode. The usefulness of the method is demonstrated in our work on the well described model system of complex I from bovine heart mitochondria. The shotgun method led to the identification and partial sequence characterization of 42 subunits representing more than 95% coverage of the complex. In particular, almost all nuclear (except MLRQ) and 5 mitochondria DNA encoded subunits (except ND4L and ND6) were identified. Furthermore, it was possible to identify 30 co-purified proteins of the inner mitochondrial membrane structurally not belonging to complex I. The method's efficiency is shown by comparing it to two classical 1 D gel-based strategies. Shotgun proteomics is less laborious, significantly faster and requires less sample material with minimal treatment, facilitating the screening for post-translational modifications and quantitative and qualitative differences of complex I subunits in genetic disorders.

Animals↗

PubMed2026

Addressing lignin composition and content via Arabidopsis arogenate dehydratase knockout and over-expression genotypes.

Following the down-selection of 14 Arabidopsis thaliana arogenate dehydratase (ADT) knockout and over-expression (OE) genotypes, the most highly contrasting quadruple knockout adt3/4/5/6 and ADT OE genotypes were subjected to proteomics, metabolomics, and scanning electron microscopy (SEM) analyses as needed, with results compared to Columbia wild-type (WT). The basal adt3/4/5/6 stem cross-sections, ∼70% lignin content reduced, exhibited buckled vessel cell walls and partially detached xylary fibers, in contrast to WT and ADT4m/5 m OE genotypes that did not. Anatomical defects primarily resulted from guaiacyl lignin level reductions in vessels with concomitant increased stem syringyl:guaiacyl (S/G) ratios. Phenylpropanoid and various upstream shikimate-chorismate pathway enzyme abundances, as well as specific monolignol oxidases (laccases/peroxidases), generally increased in adt3/4/5/6 at different stem and rosette leaf growth/development stages, relative to WT. Opposite effects were largely observed with the ADT5m OE genotype. By contrast, flavonoid and glucosinolate pathway enzyme amounts varied. Such enzyme abundance increases were overall unproductive as adt3/4/5/6 was unable to restore WT, ADT4 OE, ADT5 OE, ADT5m OE, and ADT4m/5 m OE secondary metabolite (lignin, phenylpropanoid, lignan, flavonoid, phenolic acid, and glucosinolate) levels. Conversely, ADT OE genotypes did not significantly increase programmed lignin levels or alter S/G compositions. In sum, proteomics analyses of adt3/4/5/6 and adt5 'perceived' that lignin and low molecular weight secondary metabolite amounts were not at 'programmed' levels as for WT and ADT OE genotypes but observed increases in relevant pathway protein abundances were futile. Notably though, proteomics analyses did not lead to predicting that lignin and associated biochemical pathways would have reduced metabolite levels, relative to WT and ADT OE genotypes. Genotype adt3/4/5/6, possibly the highest lignin level reduced genotype reported, did not utilize other phenolics to compensate. By contrast, the differential temporal and spatial deposition of cell wall oxidases again indicate the exquisite control over lignin deposition, and our lack of knowledge of precise lignin structure and assembly in subcellular regions of the lignified cell walls.

Lignin↗