Targeted proteome analysis of single-gene deletion strains of Saccharomyces cerevisiae lacking enzymes in the central carbon metabolism

Integrative approaches for predicting protein network perturbations through machine learning and structural characterization

Chromatin remodeling complexes, such as the Saccharomyces cerevisiae INO80 complex, exemplify how dynamic protein interaction networks govern cellular function through a balance of conserved structural modules and context-dependent functional partnerships, as revealed by integrative machine learning and structural mapping approaches. In this study, we explored the INO80 complex using machine learning to predict network changes caused by genetic deletions. Tree-based models outperformed linear approaches, highlighting non-linear relationships within the interaction network. Feature selection identified key INO80 components (e.g., Arp5, Arp8) and cross-compartment features from other remodeling complexes like SWR1 and NuA4, emphasizing shared functional pathways. Perturbation patterns aligned with biological modules, particularly those linked to telomere maintenance and aging, underscoring the functional coherence of these networks. Structural mapping revealed that not all interactions are predictable through proximity alone, particularly with Arp5 and Yta7. By combining structural insights with machine learning, we enhanced predictions of genetic perturbation effects, providing a template for analyzing cross-species homologs (e.g., human INO80) and their disease-associated variants. This integrative approach bridges the gap between static structural data and dynamic functional networks, offering a pathway to disentangle conserved mechanisms from context-dependent adaptations in chromatin biology. SIGNIFICANCE: By leveraging an innovative, integrative machine learning approach, we have successfully predicted and analyzed perturbations in the INO80 network with good accuracy and depth. Our novel combination of machine learning, perturbation analysis, and structural investigation approach has provided crucial insights into the complex's structure-function relationships, shedding new light on its pivotal roles in affected pathways such as telomere maintenance. Our findings not only enhance our understanding of the INO80 complex but also establish a powerful framework for future studies in chromatin biology and beyond. This work represents a step forward in our understanding of chromatin remodeling complexes and their diverse cellular functions, laying the groundwork for future studies that can further refine our computational approaches and experimental techniques in this field.

ΔΔG Method for Elucidating Key Control Reactions from Relative Quantification Metabolome Data: Comparative Analysis of Yeast Glycolysis

This study introduces the ΔΔG method, a novel approach to analyzing metabolic regulation using relative quantification metabolome data. The method calculates shifts in the Gibbs free energy change (ΔG) in two different metabolic states. Subsequently, key reactions controlling the metabolic flux can be identified by comparing the ΔΔG values to the reaction rates. Two case studies demonstrated the applicability of this method. First, a metabolome data set was obtained from the wild-type and single-gene-deletion mutant strains of Saccharomyces cerevisiae. The ΔΔG values of the glycolytic reactions were calculated between those of the wild-type and each mutant strain. A positive correlation was observed between the ΔΔG values of phosphofructokinase (PFK) and the approximate glycolytic flux levels. These results suggested that PFK regulates glycolytic flux. Moreover, a comparison between S. cerevisiae (Crabtree-positive yeast) and Kluyveromyces marxianus (Crabtree-negative yeast) revealed that S. cerevisiae primarily regulates glycolysis through PFK, whereas K. marxianus employs a more distributed control. The ΔΔG method provides insights into metabolic regulation that are not apparent from metabolite profiles alone and is applicable to various biological systems, particularly for analyzing glycolysis. Furthermore, the simplicity of this method makes it a valuable tool for metabolic engineering and medical research.

The proteomic landscape of genome-wide genetic perturbations

Functional genomic strategies have become fundamental for annotating gene function and regulatory networks. Here, we combined functional genomics with proteomics by quantifying protein abundances in a genome-scale knockout library in Saccharomyces cerevisiae, using data-independent acquisition mass spectrometry. We find that global protein expression is driven by a complex interplay of (1) general biological properties, including translation rate, protein turnover, the formation of protein complexes, growth rate, and genome architecture, followed by (2) functional properties, such as the connectivity of a protein in genetic, metabolic, and physical interaction networks. Moreover, we show that functional proteomics complements current gene annotation strategies through the assessment of proteome profile similarity, protein covariation, and reverse proteome profiling. Thus, our study reveals principles that govern protein expression and provides a genome-spanning resource for functional annotation.

Proteomics in Inherited Metabolic Disorders

Inherited metabolic disorders (IMD) are rare medical conditions caused by genetic defects that interfere with the body's metabolism. The clinical phenotype is highly variable and can present at any age, although it more often manifests in childhood. The number of treatable IMDs has increased in recent years, making early diagnosis and a better understanding of the natural history of the disease more important than ever. In this review, we discuss the main challenges faced in applying proteomics to the study of IMDs, and the key advances achieved in this field using tandem mass spectrometry (MS/MS). This technology enables the analysis of large numbers of proteins in different body fluids (serum, plasma, urine, saliva, tears) with a single analysis of each sample, and can even be applied to dried samples. MS/MS has thus emerged as the tool of choice for proteome characterization and has provided new insights into many diseases and biological systems. In the last 10 years, sequential window acquisition of all theoretical fragmentation spectra mass spectrometry (SWATH-MS) has emerged as an accurate, high-resolution technique for the identification and quantification of proteins differentially expressed between healthy controls and IMD patients. Proteomics is a particularly promising approach to help obtain more information on rare genetic diseases, including identification of biomarkers to aid early diagnosis and better understanding of the underlying pathophysiology to guide the development of new therapies. Here, we summarize new and emerging proteomic technologies and discuss current uses and limitations of this approach to identify and quantify proteins. Moreover, we describe the use of proteomics to identify the mechanisms regulating complex IMD phenotypes; an area of research essential to better understand these rare disorders and many other human diseases.

Increased carvone production in Escherichia coli by balancing limonene conversion enzyme expression via targeted quantification concatamer proteome analysis

(−)-Carvone is a monoterpenoid with a spearmint flavor. A sustainable biotechnological production process for (−)-carvone is desirable. Although all enzymes in (−)-carvone biosynthesis have been functionally expressed in Escherichia coli independently, the yield was low in previous studies. When cytochrome P450 limonene-6-hydroxylase (P450)/cytochrome P450 reductase (CPR) and carveol dehydrogenase (CDH) were expressed in a single strain, by-product formation (dihydrocarveol and dihydrocarvone) was detected. We hypothesized that P450 and CDH expression levels differ in E. coli. Thus, two strains independently expressing P450/CPR and CDH were mixed with different ratios, confirming increased carvone production and decreased by-product formation when CDH input was reduced. The optimum ratio of enzyme expression to maximize (−)-carvone production was determined using the proteome analysis quantification concatamer (QconCAT) method. Thereafter, a single strain expressing both P450/CPR and CDH was constructed to imitate the optimum expression ratio. The upgraded strain showed a 15-fold improvement compared to the initial strain, showing a 44 ± 6.3 mg/L (−)-carvone production from 100 mg/L (−)-limonene. Our study showed the usefulness of the QconCAT proteome analysis method for strain development in the industrial biotechnology field.

NADPH is important for isobutanol tolerance in a minimal medium of Saccharomyces cerevisiae

We showed that the isobutanol sensitivity in glucose-6-phosphate dehydrogenase-deficient cells of the yeast Saccharomyces cerevisiae was rescued by an alternative NADPH producer, acetaldehyde dehydrogenase, but not in the cells lacking 6-phosphogluconate dehydrogenase. This phenotype correlated with the intracellular NADPH/NADP+ ratio in yeast strains. Our findings indicate the importance of NADPH for the isobutanol tolerance of yeast cells.

Analysis and effect of conventional flasks in shaking culture of Escherichia coli

The circulation direct monitoring and sampling system (CDMSS) is used as a monitoring device for CO₂ and O₂ concentrations of bypass type in shake-culture flask. The CDMSS could measure k_La, an index for evaluating the performance of aerobic culture incubators, and k_G, an indicator of the degree of CO₂ ventilation in the flask gas phase. We observed that cylindrical flasks provided a different culture environment, yielded a much higher k_G than the Erlenmeyer and Sakaguchi flasks, and yielded k_La equivalent to that by Erlenmeyer flask by setting the ring-type baffle appropriately. Baffled cylindrical flask used for Escherichia coli K12 IFO3301 shake culture maintained lower CO₂ concentrations in the headspace than conventional flasks; therefore, CO₂ accumulation in the culture broth could be suppressed. Cell growth in baffled cylindrical flask (with k_La equivalent to that of the Erlenmeyer flask) was about 1.3 and 1.4 times that in the Erlenmeyer and Sakaguchi flasks, respectively. This study focused on the batch culture at the flask scale and designed the headspace environment with low CO₂ accumulation. Therefore, we conclude that redesign of flasks based on k_La and k_G may contribute to a wide range of fields employing microorganism culture.

Temporal proteome dynamics of Clostridium cellulovorans cultured with major plant cell wall polysaccharides

BACKGROUND

Clostridium cellulovorans is a mesophilic, cellulosome-producing bacterium containing 57 genomic cellulosomal enzyme-encoding genes. In addition to cellulosomal proteins, C. cellulovorans also secretes non-cellulosomal proteins to degrade plant cell wall polysaccharides. Unlike other cellulosome-producing Clostridium species, C. cellulovorans can metabolize all major plant cell wall polysaccharides (cellulose, hemicelluloses, and pectins). In this study, we performed a temporal proteome analysis of C. cellulovorans to reveal strategies underlying plant cell wall polysaccharide degradation.

RESULTS

We cultured C. cellulovorans with five different carbon sources (glucose, cellulose, xylan, galactomannan, and pectin) and performed proteome analysis on cellular and secreted proteins. In total, we identified 1895 cellular proteins and 875 secreted proteins. The identified unique carbohydrate-degrading enzymes corresponding to each carbon source were annotated to have specific activity against each carbon source. However, we identified pectate lyase as a unique enzyme in C. cellulovorans cultivated on xylan, which was not previously associated with xylan degradation. We performed k-means clustering analysis for elucidation of temporal changes of the cellular and secreted proteins in each carbon sources. We found that cellular proteins in most of the k-means clusters are involved in carbohydrate metabolism, amino acid metabolism, translation, or membrane transport. When xylan and pectin were used as the carbon sources, the most increasing k-means cluster contained proteins involved in the metabolism of cofactors and vitamins. In case of secreted proteins of C. cellulovorans cultured either on cellulose or xylan, galactomannan, and pectin, the clusters with the most increasing trend contained either 25 cellulosomal proteins and five non-cellulosomal proteins or 8-19 cellulosomal proteins and 9-16 non-cellulosomal proteins, respectively. These differences might reflect mechanisms for degrading cellulose of other carbon source. Co-abundance analysis of the secreted proteins revealed that proteases and protease inhibitors accumulated coordinately. This observation implies that the secreted protease inhibitors and proteases protect carbohydrate-degrading enzymes from an attack from the plant.

CONCLUSION

In this study, we clarified, for the first time, the temporal proteome dynamics of cellular and secreted proteins in C. cellulovorans. This data will be valuable in understanding strategies employed by C. cellulovorans for degrading major plant cell wall polysaccharides.

Monitoring of CO2 and O2 concentrations in the headspace of Sakaguchi flasks during liquid culture of microorganism

CO₂ and O₂ in the Sakaguchi flask headspace during culture was monitored via circulation direct monitoring and sampling system (CDMSS), a device with circulation bypass system. In static culture with Saccharomyces cerevisiae (circulation rate, 50 mL/min), a vertical CO₂ concentration gradient (maximum gap ~ 2% (v/v) [height from the bottom of flask 45 mm, 7%; 155 mm, 5%]) in the Sakaguchi flask headspace was observed; no concentration O₂ gradient was observed. However, shake flask culture showed vertical gradient concentrations for both CO₂ and O₂ (maximum gap of CO₂ and O₂ concentrations: 2 and 4% [heights from the bottom of flask 115 mm, 6.0 and 9.5%; 175 mm, 4.0 and 13.5%], respectively). When the CDMSS circulation rate in the Sakaguchi flask headspace was 300 or 400 mL/min, the gaseous environment was uniformly distributed so that no vertical gradient concentration was observed. In shaking culture with Escherichia coli under these conditions, CO₂ was accumulated at high concentrations in the headspace and culture broth (maximum values 8%, in the headspace; 120 mg/L, in the culture broth). Most of the accumulated CO₂ in the headspace could be removed by inserting a column packed with CO₂ adsorbent at the bypass port of the CDMSS gaseous circulation. Thus, dissolved CO₂ was maintained at a lower concentration, and the final UOD (unit optical density) value of culture was increased compared with that of the control. This study is the first to demonstrate that vertical gradients of CO₂ and O₂ concentrations exist in the headspace of Sakaguchi flask during culture.

The promise of targeted proteomics for quantitative network biology

Proteomics is a powerful tool for obtaining information on a large number of proteins with regard to their expression levels, interactions with other molecules, and posttranslational modifications. Whereas nontargeted, discovery proteomics uncovers differences in the proteomic landscape under different conditions, targeted proteomics has been developed to overcome the limitations of this approach with regard to quantitation. In addition to technical advances in instruments and informatics tools, the advent of the synthetic proteome composed of synthetic peptides or recombinant proteins has advanced the adoption of targeted proteomics across a wide range of research fields. Targeted proteomics can now be applied to measurement of the dynamics of any proteins of interest under a variety of conditions as well as to estimation of the absolute abundance or stoichiometry of proteins in a given network. Multiplexed targeted proteomics assays of high reproducibility and accuracy can provide insight at the quantitative level into entire networks that govern biological phenomena or diseases. Such assays will establish a new paradigm for data-driven science.

Application of targeted mass spectrometry in bottom-up proteomics for systems biology research

The enormous diversity of proteoforms produces tremendous complexity within cellular proteomes, facilitates intricate networks of molecular interactions, and constitutes a formidable analytical challenge for biomedical researchers. Currently, quantitative whole-proteome profiling often relies on non-targeted liquid chromatography-mass spectrometry (LC-MS), which samples proteoforms broadly, but can suffer from lower accuracy, sensitivity, and reproducibility compared with targeted LC-MS. Recent advances in bottom-up proteomics using targeted LC-MS have enabled previously unachievable identification and quantification of target proteins and posttranslational modifications within complex samples. Consequently, targeted LC-MS is rapidly advancing biomedical research, especially systems biology research in diverse areas that include proteogenomics, interactomics, kinomics, and biological pathway modeling. With the recent development of targeted LC-MS assays for nearly the entire human proteome, targeted LC-MS is positioned to enable quantitative proteomic profiling of unprecedented quality and accessibility to support fundamental and clinical research. Here we review recent applications of bottom-up proteomics using targeted LC-MS for systems biology research. SIGNIFICANCE: Advances in targeted proteomics are rapidly advancing systems biology research. Recent applications include systems-level investigations focused on posttranslational modifications (such as phosphoproteomics), protein conformation, protein-protein interaction, kinomics, proteogenomics, and metabolic and signaling pathways. Notably, absolute quantification of metabolic and signaling pathway proteins has enabled accurate pathway modeling and engineering. Integration of targeted proteomics with other technologies, such as RNA-seq, has facilitated diverse research such as the identification of hundreds of "missing" human proteins (genes and transcripts that appear to encode proteins but direct experimental evidence was lacking).