LFQRatio: A Normalization Method to Decipher Quantitative Proteome Changes in Microbial Coculture Systems.

The value of synthetic microbial communities in biotechnology is gaining traction due to their ability to undertake more complex metabolic tasks than monocultures. However, a thorough understanding of strain interactions, productivity, and stability is often required to optimize growth and scale up cultivation. Quantitative proteomics can provide valuable insights into how microbial strains adapt to changing conditions in biomanufacturing. However, current workflows and methodologies are not suitable for simple artificial coculture systems where strain ratios are dynamic. Here, we established a workflow for coculture proteomics using an exemplar system containing two members, Azotobacter vinelandii and Synechococcus elongatus. Factors affecting the quantitative accuracy of coculture proteomics were investigated, including peptide physicochemical characteristics such as molecular weight, isoelectric point, hydrophobicity, and dynamic range as well as factors relating to protein identification such as varying proteome size and shared peptides between species. Different quantification methods based on spectral counts and intensity were evaluated at the protein and cell level. We propose a new normalization method, named "LFQRatio", to reflect the relative contributions of two distinct cell types emerging from cell ratio changes during cocultivation. LFQRatio can be applied to real coculture proteomics experiments, providing accurate insights into quantitative proteome changes in each strain.

The HLA-B*57:01 allele corresponds to a very large MHC haploblock likely explaining its massive effect for HIV-1 elite control.

Introduction: We have reanalyzed the genomic data of the International Collaboration for the Genomics of HIV (ICGH), centering on HIV-1 Elite Controllers. Methods: We performed a genome-wide Association Study comparing 543 HIV Elite Controllers with 3,272 uninfected controls of European descent. Using the latest database for imputation, we analyzed 35,552 Single Nucleotide Polymorphisms (SNPs) within the Major Histocompatibility Complex (MHC) region. Results: Our analysis identified 2,626 SNPs significantly associated (p<5. 10-8) with elite control of HIV-1 infection, including well-established MHC signals such as the rs2395029-G allele which tags HLA-B*57:01. A thorough investigation of SNPs in linkage disequilibrium with rs2395029 revealed an extensive haploblock spanning 1.9 megabases in the MHC region tagging HLA-B*57:01, comprising 379 SNP alleles impacting 72 genes. This haploblock contains damaging variations in proteins like NOTCH4 and DXO and is also associated with a strong differential pattern of expression of multiple MHC genes such as HLA-B, MICB, and ZBTB12. The study was expanded to include two cohorts of seropositive African-American individuals, where a haploblock tagging the HLA-B*57:03 allele was similarly associated with control of viral load. The mRNA expression profile of this haploblock in African Americans closely mirrored that in the European cohort. Discussion: These findings suggest that additional molecular mechanisms beyond the conventional antigen-presenting role of class I HLA molecules may contribute to the observed influence of HLA-B*57:01/B*57:03 alleles on HIV-1 elite control. Overall, this study has uncovered a large haploblock associated with HLA-B*57 alleles, providing novel insights into their massive effect on HIV-1 elite control.

Gene expression profiling of peripheral blood mononuclear cells from women with cervical lesions reveals new markers of cancer.

Cervical cancer (CC) is a multifactorial disease of which human papillomavirus (HPV) is the main etiological agent. Despite cervical Pap smear screening and anti­HPV vaccination, CC remains a major public health issue. Identification of specific gene expression signatures in the blood could allow better insight into the immune response of CC and could provide valuable information for the development of novel biomarkers. The present study performed a transcriptomic analysis of peripheral blood mononuclear cells (PBMCs) from Senegalese patients with CC (n=31), low­grade cervical intraepithelial neoplasia (CIN1; n=27) and from healthy control (CTR) subjects (n=29). Individuals in the CIN1 and CTR groups exhibited similar patterns in gene expression. A total of 182 genes were revealed to be differentially expressed in patients with CC compared with individuals in the CIN1 and CTR groups. The IL1R2, IL18R1, MMP9 and FKBP5 genes were the most upregulated, whereas the T­cell receptor α gene TRA was the most downregulated in the CC group compared with in the CIN1 and CTR groups. The pathway enrichment analysis of the differentially expressed genes revealed pathways directly and indirectly linked to inflammation. To the best of our knowledge, the present study is the first large transcriptomic study on CC performed using PBMCs from African women; the results revealed the involvement of genes and pathways related to inflammation, most notably the IL­1 pathway, and the involvement of downregulation of the T­cell receptor α, a key component of the immune response. Several of the stated genes have already been reported in other cancer studies as putative blood biomarkers, thus reinforcing the requirement for deeper investigation. These findings may aid in the development of innovative clinical biomarkers for CC prevention and should be further replicated in other populations.

Linear epitope mapping of the humoral response against SARS-CoV-2 in two independent African cohorts.

Profiling of the antibody responses to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) proteins in African populations is scarce. Here, we performed a detailed IgM and IgG epitope mapping study against 487 peptides covering SARS-CoV-2 wild-type structural proteins. A panel of 41 pre-pandemic and 82 COVID-19 RT-PCR confirmed sera from Madagascar and Senegal were used. We found that the main 36 immunodominant linear epitopes identified were (i) similar in both countries, (ii) distributed mainly in the Spike and the Nucleocapsid proteins, (iii) located outside the RBD and NTD regions where most of the reported SARS-CoV-2 variant mutations occur, and (iv) identical to those reported in European, North American, and Asian studies. Within the severe group, antibody levels were inversely correlated with the viral load. This first antibody epitope mapping study performed in patients from two African countries may be helpful to guide rational peptide-based diagnostic assays or vaccine development.

Functional characterization of 5p15.33 risk locus in uveal melanoma reveals rs452384 as a functional variant and NKX2.4 as an allele-specific interactor.

The TERT/CLPTM1L risk locus on chromosome 5p15.33 is a pleiotropic cancer risk locus in which multiple independent risk alleles have been identified, across well over ten cancer types. We previously conducted a genome-wide association study in uveal melanoma (UM), which uncovered a role for the TERT/CLPTM1L risk locus in this intraocular tumor and identified multiple highly correlated risk alleles. Aiming to unravel the biological mechanisms in UM of this locus, which contains a domain enriched in active chromatin marks and enhancer elements, we demonstrated the allele-specific enhancer activity of this risk region using reporter assays. In UM, we identified the functional variant rs452384, of which the C risk allele is associated with higher gene expression, increased CLPTM1L expression in UM tumors, and a longer telomere length in peripheral blood mononuclear cells. Electrophoretic mobility shift assays and quantitative mass spectrometry identified NKX2.4 as an rs452384-T-specific binding protein, whereas GATA4 preferentially interacted with rs452384-C. Knockdown of NKX2.4 but not GATA4 resulted in increased TERT and CLPTM1L expression. In summary, the UM risk conferred by the 5p locus is at least partly due to rs452384, for which NKX2.4 presents strong differential binding activity and regulates CLPTM1L and TERT expression. Altogether, our work unraveled some of the complex regulatory mechanisms at the 5p15.33 susceptibility region in UM, and this might also shed light on shared mechanisms with other tumor types affected by this susceptibility region.

Different Pigmentation Risk Loci for High-Risk Monosomy 3 and Low-Risk Disomy 3 Uveal Melanomas.

BACKGROUND: Uveal melanoma (UM), a rare malignant tumor of the eye, is predominantly observed in populations of European ancestry. UMs carrying a monosomy 3 (M3) frequently relapse mainly in the liver, whereas UMs with disomy 3 (D3) are associated with more favorable outcome. Here, we explored the UM genetic predisposition factors in a large genome-wide association study (GWAS) of 1142 European UM patients and 882 healthy controls . METHODS: We combined 2 independent datasets (Global Screening Array) with the dataset described in a previously published GWAS in UM (Omni5 array), which were imputed separately and subsequently merged. Patients were stratified according to their chromosome 3 status, and identified UM risk loci were tested for differential association with M3 or D3 subgroups. All statistical tests were 2-sided. RESULTS: We recapitulated the previously identified risk locus on chromosome 5 on CLPTM1L (rs421284: odds ratio [OR] =1.58, 95% confidence interval [CI] = 1.35 to 1.86; P = 1.98 × 10-8) and identified 2 additional risk loci involved in eye pigmentation: IRF4 locus on chromosome 6 (rs12203592: OR = 1.76, 95% CI = 1.44 to 2.16; P = 3.55 × 10-8) and HERC2 locus on chromosome 15 (rs12913832: OR= 0.57, 95% CI = 0.48 to 0.67; P = 1.88 × 10-11). The IRF4 rs12203592 single-nucleotide polymorphism was found to be exclusively associated with risk for the D3 UM subtype (ORD3 = 2.73, 95% CI = 1.87 to 3.97; P = 1.78 × 10-7), and the HERC2 rs12913832 single-nucleotide polymorphism was exclusively associated with risk for the M3 UM subtype (ORM3 = 2.43, 95% CI = 1.79 to 3.29; P = 1.13 × 10-8). However, the CLPTM1L risk locus was equally statistically significant in both subgroups. CONCLUSIONS: This work identified 2 additional UM risk loci known for their role in pigmentation. Importantly, we demonstrate that UM tumor biology and metastatic potential are influenced by patients' genetic backgrounds.

HLA-check: evaluating HLA data from SNP information.

BACKGROUND: The major histocompatibility complex (MHC) region of the human genome, and specifically the human leukocyte antigen (HLA) genes, play a major role in numerous human diseases. With the recent progress of sequencing methods (eg, Next-Generation Sequencing, NGS), the accurate genotyping of this region has become possible but remains relatively costly. In order to obtain the HLA information for the millions of samples already genotyped by chips in the past ten years, efficient bioinformatics tools, such as SNP2HLA or HIBAG, have been developed that infer HLA information from the linkage disequilibrium existing between HLA alleles and SNP markers in the MHC region. RESULTS: In this study, we first used ShapeIT and Impute2 to implement an imputation method akin to SNP2HLA and found a comparable quality of imputation on a European dataset. More importantly, we developed a new tool, HLA-check, that allows for the detection of aberrant HLA allele calling with regard to the SNP genotypes in the region. Adding this tool to the HLA imputation software increases dramatically their accuracy, especially for HLA class I genes. CONCLUSION: Overall, HLA-check was able to identify a limited number of implausible HLA typings (less than 10%) in a population, and these samples can then either be removed or be retyped by NGS for HLA association analysis.

A new 3p25 locus is associated with liver fibrosis progression in human immunodeficiency virus/hepatitis C virus-coinfected patients.

There is growing evidence that human genetic variants contribute to liver fibrosis in subjects with hepatitis C virus (HCV) monoinfection, but this aspect has been little investigated in patients coinfected with HCV and human immunodeficiency virus (HIV). We performed the first genome-wide association study of liver fibrosis progression in patients coinfected with HCV and HIV, using the well-characterized French National Agency for Research on AIDS and Viral Hepatitis CO13 HEPAVIH cohort. Liver fibrosis was assessed by elastography (FibroScan), providing a quantitative fibrosis score. After quality control, a genome-wide association study was conducted on 289 Caucasian patients, for a total of 8,426,597 genotyped (Illumina Omni2.5 BeadChip) or reliably imputed single-nucleotide polymorphisms. Single-nucleotide polymorphisms with P values <10-6 were investigated in two independent replication cohorts of European patients infected with HCV alone. Two signals of genome-wide significance (P < 5 × 10-8 ) were obtained. The first, on chromosome 3p25 and corresponding to rs61183828 (P = 3.8 × 10-9 ), was replicated in the two independent cohorts of patients with HCV monoinfection. The cluster of single-nucleotide polymorphisms in linkage disequilibrium with rs61183828 was located close to two genes involved in mechanisms affecting both cell signaling and cell structure (CAV3) or HCV replication (RAD18). The second signal, obtained with rs11790131 (P = 9.3 × 10-9 ) on chromosome region 9p22, was not replicated. CONCLUSION: This genome-wide association study identified a new locus associated with liver fibrosis severity in patients with HIV/HCV coinfection, on chromosome 3p25, a finding that was replicated in patients with HCV monoinfection; these results provide new relevant hypotheses for the pathogenesis of liver fibrosis in patients with HIV/HCV coinfection that may help define new targets for drug development or new prognostic tests, to improve patient care. (Hepatology 2016;64:1462-1472).

Quantitative proteomic analysis of the influence of lignin on biofuel production by Clostridium acetobutylicum ATCC 824.

BACKGROUND: Clostridium acetobutylicum has been a focus of research because of its ability to produce high-value compounds that can be used as biofuels. Lignocellulose is a promising feedstock, but the lignin-cellulose-hemicellulose biomass complex requires chemical pre-treatment to yield fermentable saccharides, including cellulose-derived cellobiose, prior to bioproduction of acetone-butanol-ethanol (ABE) and hydrogen. Fermentation capability is limited by lignin and thus process optimization requires knowledge of lignin inhibition. The effects of lignin on cellular metabolism were evaluated for C. acetobutylicum grown on medium containing either cellobiose only or cellobiose plus lignin. Microscopy, gas chromatography and 8-plex iTRAQ-based quantitative proteomic technologies were applied to interrogate the effect of lignin on cellular morphology, fermentation and the proteome. RESULTS: Our results demonstrate that C. acetobutylicum has reduced performance for solvent production when lignin is present in the medium. Medium supplemented with 1 g L(-1) of lignin led to delay and decreased solvents production (ethanol; 0.47 g L(-1) for cellobiose and 0.27 g L(-1) for cellobiose plus lignin and butanol; 0.13 g L(-1) for cellobiose and 0.04 g L(-1) for cellobiose plus lignin) at 20 and 48 h, respectively, resulting in the accumulation of acetic acid and butyric acid. Of 583 identified proteins (FDR < 1 %), 328 proteins were quantified with at least two unique peptides. Up- or down-regulation of protein expression was determined by comparison of exponential and stationary phases of cellobiose in the presence and absence of lignin. Of relevance, glycolysis and fermentative pathways were mostly down-regulated, during exponential and stationary growth phases in presence of lignin. Moreover, proteins involved in DNA repair, transcription/translation and GTP/ATP-dependent activities were also significantly affected and these changes were associated with altered cell morphology. CONCLUSIONS: This is the first comprehensive analysis of the cellular responses of C. acetobutylicum to lignin at metabolic and physiological levels. These data will enable targeted metabolic engineering strategies to optimize biofuel production from biomass by overcoming limitations imposed by the presence of lignin.

Reduced keratin expression in colorectal neoplasia and associated fields is reversible by diet and resection.

BACKGROUND: Patients with adenomatous colonic polyps are at increased risk of developing further polyps suggesting field-wide alterations in cancer predisposition. The current study aimed to identify molecular alterations in the normal mucosa in the proximity of adenomatous polyps and to assess the modulating effect of butyrate, a chemopreventive compound produced by fermentation of dietary residues. METHODS: A cross-sectional study was undertaken in patients with adenomatous polyps: biopsy samples were taken from the adenoma, and from macroscopically normal mucosa on the contralateral wall to the adenoma and from the mid-sigmoid colon. In normal subjects biopsies were taken from the mid-sigmoid colon. Biopsies were frozen for proteomic analysis or formalin-fixed for immunohistochemistry. Proteomic analysis was undertaken using iTRAQ workflows followed by bioinformatics analyses. A second dietary fibre intervention study arm used the same endpoints and sampling strategy at the beginning and end of a high-fibre intervention. RESULTS: Key findings were that keratins 8, 18 and 19 were reduced in expression level with progressive proximity to the lesion. Lesional tissue exhibited multiple K8 immunoreactive bands and overall reduced levels of keratin. Biopsies from normal subjects with low faecal butyrate also showed depressed keratin expression. Resection of the lesion and elevation of dietary fibre intake both appeared to restore keratin expression level. CONCLUSION: Changes in keratin expression associate with progression towards neoplasia, but remain modifiable risk factors. Dietary strategies may improve secondary chemoprevention. TRIAL REGISTRATION NUMBER: ISRCTN90852168.

Identification of Genes Whose Expression Profile Is Associated with Non-Progression towards AIDS Using eQTLs.

BACKGROUND: Many genome-wide association studies have been performed on progression towards the acquired immune deficiency syndrome (AIDS) and they mainly identified associations within the HLA loci. In this study, we demonstrate that the integration of biological information, namely gene expression data, can enhance the sensitivity of genetic studies to unravel new genetic associations relevant to AIDS. METHODS: We collated the biological information compiled from three databases of expression quantitative trait loci (eQTLs) involved in cells of the immune system. We derived a list of single nucleotide polymorphisms (SNPs) that are functional in that they correlate with differential expression of genes in at least two of the databases. We tested the association of those SNPs with AIDS progression in two cohorts, GRIV and ACS. Tests on permuted phenotypes of the GRIV and ACS cohorts or on randomised sets of equivalent SNPs allowed us to assess the statistical robustness of this method and to estimate the true positive rate. RESULTS: Eight genes were identified with high confidence (p = 0.001, rate of true positives 75%). Some of those genes had previously been linked with HIV infection. Notably, ENTPD4 belongs to the same family as CD39, whose expression has already been associated with AIDS progression; while DNAJB12 is part of the HSP90 pathway, which is involved in the control of HIV latency. Our study also drew our attention to lesser-known functions such as mitochondrial ribosomal proteins and a zinc finger protein, ZFP57, which could be central to the effectiveness of HIV infection. Interestingly, for six out of those eight genes, down-regulation is associated with non-progression, which makes them appealing targets to develop drugs against HIV.

Advances in proteomics for production strain analysis.

Proteomics is the large-scale study and analysis of proteins, directed to analysing protein function in a cellular context. Since the vast majority of the processes occurring in a living cell rely on protein activity, proteomics offer a unique vantage point from which researchers can dissect, characterise, understand and manipulate biological systems. When developing a production strain, proteomics offers a versatile toolkit of analytical techniques. In this commentary, we highlight a number of recent developments in this field using three industrially relevant case studies: targeted proteomic analysis of heterologous pathways in Escherichia coli, biofuel production in Synechocystis PCC6803 and proteomic investigations of lignocellulose degradation. We conclude by discussing future developments in proteomics that will impact upon metabolic engineering and process monitoring of bio-producer strains.

Quantitation with chemical tagging reagents in biomarker studies.

Isobaric tags for relative and absolute quantitation (iTRAQ), Tandem Mass Tags (TMT) and related chemical tag reagents provide analytical platforms for quantitative proteomics applied to clinical samples. In this Viewpoint article, applications for discovery and targeted modes are discussed with an emphasis on study design and technical considerations in biomarker analysis. The evolution and promise of emerging, related strategies are also discussed. It should be noted that iTRAQ and TMT users contributed to the key debates in the biomarker field, to define strategies for biomarker discovery for identification of clinical biomarkers, and continue to inform design of verification and validation assays via implementation of non-isobaric variants for targeted analyses.

Evidence after imputation for a role of MICA variants in nonprogression and elite control of HIV type 1 infection.

Past genome-wide association studies (GWAS) involving individuals with AIDS have mainly identified associations in the HLA region. Using the latest software, we imputed 7 million single-nucleotide polymorphisms (SNPs)/indels of the 1000 Genomes Project from the GWAS-determined genotypes of individuals in the Genomics of Resistance to Immunodeficiency Virus AIDS nonprogression cohort and compared them with those of control cohorts. The strongest signals were in MICA, the gene encoding major histocompatibility class I polypeptide-related sequence A (P = 3.31 × 10(-12)), with a particular exonic deletion (P = 1.59 × 10(-8)) in full linkage disequilibrium with the reference HCP5 rs2395029 SNP. Haplotype analysis also revealed an additive effect between HLA-C, HLA-B, and MICA variants. These data suggest a role for MICA in progression and elite control of human immunodeficiency virus type 1 infection.

Synthetic microbial ecosystems for biotechnology.

Most highly controlled and specific applications of microorganisms in biotechnology involve pure cultures. Maintaining single strain cultures is important for industry as contaminants can reduce productivity and lead to longer "down-times" during sterilisation. However, microbes working together provide distinct advantages over pure cultures. They can undertake more metabolically complex tasks, improve efficiency and even expand applications to open systems. By combining rapidly advancing technologies with ecological theory, the use of microbial ecosystems in biotechnology will inevitably increase. This review provides insight into the use of synthetic microbial communities in biotechnology by applying the engineering paradigm of measure, model, manipulate and manufacture, and illustrate the emerging wider potential of the synthetic ecology field. Systems to improve biofuel production using microalgae are also discussed.

Archaeal signal transduction: impact of protein phosphatase deletions on cell size, motility, and energy metabolism in Sulfolobus acidocaldarius.

In this study, the in vitro and in vivo functions of the only two identified protein phosphatases, Saci-PTP and Saci-PP2A, in the crenarchaeal model organism Sulfolobus acidocaldarius were investigated. Biochemical characterization revealed that Saci-PTP is a dual-specific phosphatase (against pSer/pThr and pTyr), whereas Saci-PP2A exhibited specific pSer/pThr activity and inhibition by okadaic acid. Deletion of saci_pp2a resulted in pronounced alterations in growth, cell shape and cell size, which could be partially complemented. Transcriptome analysis of the three strains (Δsaci_ptp, Δsaci_pp2a and the MW001 parental strain) revealed 155 genes that were differentially expressed in the deletion mutants, and showed significant changes in expression of genes encoding the archaella (archaeal motility structure), components of the respiratory chain and transcriptional regulators. Phosphoproteome studies revealed 801 unique phosphoproteins in total, with an increase in identified phosphopeptides in the deletion mutants. Proteins from most functional categories were affected by phosphorylation, including components of the motility system, the respiratory chain, and regulatory proteins. In the saci_pp2a deletion mutant the up-regulation at the transcript level, as well as the observed phosphorylation pattern, resembled starvation stress responses. Hypermotility was also observed in the saci_pp2a deletion mutant. The results highlight the importance of protein phosphorylation in regulating essential cellular processes in the crenarchaeon S. acidocaldarius.

A cool tool for hot and sour Archaea: proteomics of Sulfolobus solfataricus.

In recent years, much progress has been made in proteomic studies to unravel metabolic pathways and basic cellular processes. This is especially interesting for members of the Archaea, the third domain of life. Archaea exhibit extraordinary features and many of their cultivable representatives are adaptable to extreme environments. Archaea harbor many unique traits besides bacterial attributes, such as size, shape, and DNA structure and eukaryal characteristics like information processing. Sulfolobus solfataricus P2, a thermoacidophilic archaeal representative, is a well-established model organism adapted to low-pH environments (pH 2-3) and high temperatures (80°C). The genome has a size of 3 Mbp and its sequence has been deciphered. Approximately 3033 predicted open reading frames have been identified and the genome is characterized by a great number of diverse insertion sequence elements. In unraveling the organisms' metabolism and lifestyle, proteomic analyses have played a major role. Much effort has been directed at this organism and is reviewed here. With the help of proteomics, unique metabolic pathways were resolved in S. solfataricus, targets for regulatory protein phosphorylation identified, and cellular responses upon virus infection as well as oxidative stress analyzed.

Inverse metabolic engineering to improve Escherichia coli as an N-glycosylation host.

An inverse metabolic engineering strategy was used to select for Escherichia coli cells with an increased capability to N-glycosylate a specific target protein. We developed a screen for E. coli cells containing extra-chromosomal DNA fragments for improved ability to add precise sugar groups onto the AcrA protein using the glycosylation system from Campylobacter jejuni. Four different sized (1, 2, 4, and 8 kb) genomic DNA libraries were screened, and the sequences that conferred a yield advantage were determined. These advantageous genomic fragments were mapped onto the E. coli W3110 chromosome. Five candidate genes (identified across two or more libraries) were subsequently selected for forward engineering verification in E. coli CLM24 cells, utilizing a combination of internal standards for absolute quantitation and pseudo-selective reaction monitoring (pSRM) and Western blotting validation. An increase in glycosylated protein was quantified in cells overexpressing 4-α-glucantransferase and a phosphoenolpyruvate-dependent sugar phosphotransferase system, amounting to a 3.8-fold (engineered cells total = 5.3 mg L(-1) ) and 6.7-fold (engineered cells total = 9.4 mg L(-1) ) improvement compared to control cells, respectively. Furthermore, increased glycosylation efficiency was observed in cells overexpressing enzymes involved with glycosylation precursor synthesis, enzymes 1-deoxyxylulose-5-phosphate synthase (1.3-fold) and UDP-N-acetylglucosamine pyrophosphorylase (1.6-fold). To evaluate the wider implications of the engineering, we tested a modified Fc fragment of an IgG antibody as the target glycoprotein with two of our engineered cells, and achieved a ca. 75% improved glycosylation efficiency.

Opportunities for protein interaction network-guided cellular engineering.

As we move further into the postgenomics age where the mountain of systems biology-generated data keeps growing, as does the number of genomes that have been sequenced, we have the exciting opportunity to understand more deeply the biology of important systems, those that are amenable to genetic manipulation and metabolic engineering. This is, of course, if we can make 'head or tail' of what we have measured and use this for robust predictions. The use of modern mass spectrometry tools has greatly facilitated our understanding of which proteins are present in a particular phenotype, their relative and absolute abundances and their state of modifications. Coupled with modern bioinformatics and systems biology modelling tools, this has the opportunity of not just providing information and understanding but also to provide targets for engineering and suggest new genetic/metabolic designs. Cellular engineering, whether it be via metabolic engineering, synthetic biology or a combination of both approaches, offers exciting potential for biotechnological exploitation in fields as diverse as medicine and energy as well as fine and bulk chemicals production. At the heart of such effective designs, proteins' interactions with other proteins or with DNA will become increasingly important. In this work, we examine the work done until now in protein-protein interactions and how this network knowledge can be used to inform ambitious cellular engineering strategies. Some examples demonstrating small molecules/biofuels and biopharmaceuticals applications are presented.

HILIC- and SCX-based quantitative proteomics of Chlamydomonas reinhardtii during nitrogen starvation induced lipid and carbohydrate accumulation.

Nitrogen starvation induced changes in carbohydrate and lipid content is described in several algal species. Although these phenotypic changes are desirable, such manipulations also significantly deteriorate culture health, ultimately halting growth. To optimize biofuel production from algae, it is desirable to induce lipid accumulation without compromising cell growth and survival. In this study, we utilized an 8-plex iTRAQ-based proteomic approach to assess the model alga Chlamydomonas reinhardtii CCAP 11/32CW15+ under nitrogen starvation. First-dimension fractionation was conducted using HILIC and SCX. A total of 587 proteins were identified (≥3 peptides) of which 71 and 311 were differentially expressed at significant levels (p<0.05), during nitrogen stress induced carbohydrate and lipid production, respectively. Forty-seven percent more changes with significance were observed with HILIC compared to SCX. Several trends were observed including increase in energy metabolism, decrease in translation machinery, increase in cell wall production and a change of balance between photosystems I and II. These findings point to a severely compromised system where lipid is accumulated at the expense of normal functioning of the organism, suggesting that a more informed and controlled method of lipid induction than gross nutrient manipulation would be needed for development of sustainable processes.