Engineering cell-free systems by chemoproteomic-assisted phenotypic screening

Phenotypic screening is a valuable tool to both understand and engineer complex biological systems. We demonstrate the functionality of this approach in the development of cell-free protein synthesis (CFPS) technology. Phenotypic screening identified numerous compounds that enhanced protein production in yeast lysate CFPS reactions. Notably, many of these were competitive ATP kinase inhibitors, with the exploitation of their inherent substrate promiscuity redirecting ATP flux towards heterologous protein expression. Chemoproteomic-guided strain engineering partially phenocopied drug effects, with a 30% increase in protein yield observed upon deletion of the ATP-consuming SSA1 component of the HSP70 chaperone. Moreover, drug-mediated metabolic rewiring coupled with template optimization generated the highest protein yields in yeast CFPS to date using a hitherto less efficient, but more cost-effective glucose energy regeneration system. Our approach highlights the utility of target-agnostic phenotypic screening and target identification to deconvolute cell-lysate complexity, adding to the expanding repertoire of strategies for improving CFPS.

Protocol for structural modeling of antibody to human leukocyte antigen interaction using discovery and targeted cross-linking mass spectrometry

Cross-linking mass spectrometry (XL-MS) provides low-resolution structural information to model protein structures. Here, we present a protocol to identify cross-links of purified antibody binding to purified human leukocyte antigen (HLA). We describe steps for using a discovery-based XL-MS approach followed by a targeted XL-MS approach. We then detail procedures for using the identified cross-links with other structural data for molecular docking of the antibody to HLA. This protocol has applications for modeling the interacting structure of purified antibody to antigen. For complete details on the use and execution of this protocol, please refer to Ser et al.1.

A Malassezia pseudoprotease dominates the secreted hydrolase landscape and is a potential allergen on skin

Malassezia globosa is abundant and prevalent on sebaceous areas of the human skin. Genome annotation reveals that M. globosa possesses a repertoire of secreted hydrolytic enzymes relevant for lipid and protein metabolism. However, the functional significance of these enzymes is uncertain and presence of these genes in the genome does not always translate to expression at the cutaneous surface. In this study we utilized targeted RNA sequencing from samples isolated directly from the skin to quantify gene expression of M. globosa secreted proteases, lipases, phospholipases and sphingomyelinases. Our findings indicate that the expression of these enzymes is dynamically regulated by the environment in which the fungus resides, as different growth phases of the planktonic culture of M. globosa show distinct expression levels. Furthermore, we observed significant differences in the expression of these enzymes in culture compared to healthy sebaceous skin sites. By examining the in situ gene expression of M. globosa's secreted hydrolases, we identified a predicted aspartyl protease, MGL_3331, which is highly expressed on both healthy and disease-affected dermatological sites. However, molecular modeling and biochemical studies revealed that this protein has a non-canonical active site motif and lacks measurable proteolytic activity. This pseudoprotease MGL_3331 elicits a heightened IgE-reactivity in blood plasma isolated from patients with atopic dermatitis compared to healthy individuals and invokes a pro-inflammatory response in peripheral blood mononuclear cells. Overall, our study highlights the importance of studying fungal proteins expressed in physiologically relevant environments and underscores the notion that secreted inactive enzymes may have important functions in influencing host immunity.

Molecular basis for Nse5-6 mediated regulation of Smc5/6 functions

The Smc5/6 complex (Smc5/6) is important for genome replication and repair in eukaryotes. Its cellular functions are closely linked to the ATPase activity of the Smc5 and Smc6 subunits. This activity requires the dimerization of the motor domains of the two SMC subunits and is regulated by the six non-SMC subunits (Nse1 to Nse6). Among the NSEs, Nse5 and Nse6 form a stable subcomplex (Nse5-6) that dampens the ATPase activity of the complex. However, the underlying mechanisms and biological significance of this regulation remain unclear. Here, we address these issues using structural and functional studies. We determined cryo-EM structures of the yeast Smc5/6 derived from complexes consisting of either all eight subunits or a subset of five subunits. Both structures reveal that Nse5-6 associates with Smc6's motor domain and the adjacent coiled-coil segment, termed the neck region. Our structural analyses reveal that this binding is compatible with motor domain dimerization but results in dislodging the Nse4 subunit from the Smc6 neck. As the Nse4-Smc6 neck interaction favors motor domain engagement and thus ATPase activity, Nse6's competition with Nse4 can explain how Nse5-6 disfavors ATPase activity. Such regulation could in principle differentially affect Smc5/6-mediated processes depending on their needs of the complex's ATPase activity. Indeed, mutagenesis data in cells provide evidence that the Nse6-Smc6 neck interaction is important for the resolution of DNA repair intermediates but not for replication termination. Our results thus provide a molecular basis for how Nse5-6 modulates the ATPase activity and cellular functions of Smc5/6.

Structural basis of peptide secretion for Quorum sensing by ComA

Quorum sensing (QS) is a crucial regulatory mechanism controlling bacterial signalling and holds promise for novel therapies against antimicrobial resistance. In Gram-positive bacteria, such as Streptococcus pneumoniae, ComA is a conserved efflux pump responsible for the maturation and secretion of peptide signals, including the competence-stimulating peptide (CSP), yet its structure and function remain unclear. Here, we functionally characterize ComA as an ABC transporter with high ATP affinity and determined its cryo-EM structures in the presence or absence of CSP or nucleotides. Our findings reveal a network of strong electrostatic interactions unique to ComA at the intracellular gate, a putative binding pocket for two CSP molecules, and negatively charged residues facilitating CSP translocation. Mutations of these residues affect ComA's peptidase activity in-vitro and prevent CSP export in-vivo. We demonstrate that ATP-Mg2+ triggers the outward-facing conformation of ComA for CSP release, rather than ATP alone. Our study provides molecular insights into the QS signal peptide secretion, highlighting potential targets for QS-targeting drugs.

Hybrid structural modeling of alloantibody binding to human leukocyte antigen with rapid and reproducible cross-linking mass spectrometry

Alloantibody recognition of donor human leukocyte antigen (HLA) is associated with poor clinical transplantation outcomes. However, the molecular and structural basis for the alloantibody-HLA interaction is not well understood. Here, we used a hybrid structural modeling approach on a previously studied alloantibody-HLA interacting pair with inputs from ab initio, in silico, and in vitro data. Highly reproducible cross-linking mass spectrometry data were obtained with both discovery- and targeted mass spectrometry-based approaches approaches. The cross-link information was then used together with predicted antibody Fv structure, predicted antibody paratope, and in silico-predicted interacting surface to model the antibody-HLA interaction. This hybrid structural modeling approach closely recapitulates the key interacting residues from a previously solved crystal structure of an alloantibody-HLA-A∗11:01 pair. These results suggest that a predictive-based hybrid structural modeling approach supplemented with cross-linking mass spectrometry data can provide functionally relevant structural models to understand the structural basis of antibody-HLA mismatch in transplantation.

Detection of Bacterial Neutral Ceramidase in Diabetic Foot Ulcers with an Optimized Substrate and Chemoenzymatic Probes

Ceramidases (CDases) are important in controlling skin barrier integrity by regulating ceramide composition and affording downstream signal molecules. While the functions of epidermal CDases are known, roles of neutral CDases secreted by skin-residing microbes are undefined. Here, we developed a one-step fluorogenic substrate, S-B, for specific detection of bacterial CDase activity and inhibitor screening. We identified a non-hydrolyzable substrate mimic, C6, as the best hit. Based on C6, we designed a photoaffinity probe, JX-1, which efficiently detects bacterial CDases. Using JX-1, we identified endogenous low-abundance PaCDase in a P. aeruginosa monoculture and in a mixed skin bacteria culture. Harnessing both S-B and JX-1, we found that CDase activity positively correlates with the relative abundance of P. aeruginosa and is negatively associated with wound area reduction in clinical diabetic foot ulcer patient samples. Overall, our study demonstrates that bacterial CDases are important regulators of skin ceramides and potentially play a role in wound healing.

Integrative Proteogenomics Using ProteomeGenerator2

Recent advances in nucleic acid sequencing now permit rapid and genome-scale analysis of genetic variation and transcription, enabling population-scale studies of human biology, disease, and diverse organisms. Likewise, advances in mass spectrometry proteomics now permit highly sensitive and accurate studies of protein expression at the whole proteome-scale. However, most proteomic studies rely on consensus databases to match spectra to peptide and protein sequences, and thus remain limited to the analysis of canonical protein sequences. Here, we develop ProteomeGenerator2 (PG2), based on the scalable and modular ProteomeGenerator framework. PG2 integrates genome and transcriptome sequencing to incorporate protein variants containing amino acid substitutions, insertions, and deletions, as well as noncanonical reading frames, exons, and other variants caused by genomic and transcriptomic variation. We benchmarked PG2 using synthetic data and genomic, transcriptomic, and proteomic analysis of human leukemia cells. PG2 can be integrated with current and emerging sequencing technologies, assemblers, variant callers, and mass spectral analysis algorithms, and is available open-source from https://github.com/kentsisresearchgroup/ProteomeGenerator2.

Dependency of NELF-E-SLUG-KAT2B epigenetic axis in breast cancer carcinogenesis

Cancer cells undergo transcriptional reprogramming to drive tumor progression and metastasis. Using cancer cell lines and patient-derived tumor organoids, we demonstrate that loss of the negative elongation factor (NELF) complex inhibits breast cancer development through downregulating epithelial-mesenchymal transition (EMT) and stemness-associated genes. Quantitative multiplexed Rapid Immunoprecipitation Mass spectrometry of Endogenous proteins (qPLEX-RIME) further reveals a significant rewiring of NELF-E-associated chromatin partners as a function of EMT and a co-option of NELF-E with the key EMT transcription factor SLUG. Accordingly, loss of NELF-E leads to impaired SLUG binding on chromatin. Through integrative transcriptomic and genomic analyses, we identify the histone acetyltransferase, KAT2B, as a key functional target of NELF-E-SLUG. Genetic and pharmacological inactivation of KAT2B ameliorate the expression of EMT markers, phenocopying NELF ablation. Elevated expression of NELF-E and KAT2B is associated with poorer prognosis in breast cancer patients, highlighting the clinical relevance of our findings. Taken together, we uncover a crucial role of the NELF-E-SLUG-KAT2B epigenetic axis in breast cancer carcinogenesis.

Integrative proteogenomics using ProteomeGenerator2

Recent advances in nucleic acid sequencing now permit rapid and genome-scale analysis of genetic variation and transcription, enabling population-scale studies of human biology, disease, and diverse organisms. Likewise, advances in mass spectrometry proteomics now permit highly sensitive and accurate studies of protein expression at the whole proteome-scale. However, most proteomic studies rely on consensus databases to match spectra to peptide and proteins sequences, and thus remain limited to the analysis of canonical protein sequences. Here, we develop ProteomeGenerator2 (PG2), based on the scalable and modular ProteomeGenerator framework. PG2 integrates genome and transcriptome sequencing to incorporate protein variants containing amino acid substitutions, insertions, and deletions, as well as non-canonical reading frames, exons, and other variants caused by genomic and transcriptomic variation. We benchmarked PG2 using synthetic data and genomic, transcriptomic, and proteomic analysis of human leukemia cells. PG2 can be integrated with current and emerging sequencing technologies, assemblers, variant callers, and mass spectral analysis algorithms, and is available open-source from https://github.com/kentsisresearchgroup/ProteomeGenerator2 .

Optimized Cross-Linking Mass Spectrometry for in Situ Interaction Proteomics

Recent development of mass spectrometer cleavable protein cross-linkers and algorithms for their spectral identification now permits large-scale cross-linking mass spectrometry (XL-MS). Here, we optimized the use of cleavable disuccinimidyl sulfoxide (DSSO) cross-linker for labeling native protein complexes in live human cells. We applied a generalized linear mixture model to calibrate cross-link peptide-spectra matching (CSM) scores to control the sensitivity and specificity of large-scale XL-MS. Using specific CSM score thresholds to control the false discovery rate, we found that higher-energy collisional dissociation (HCD) and electron transfer dissociation (ETD) can both be effective for large-scale XL-MS protein interaction mapping. We found that the coverage of protein-protein interaction maps is significantly improved through the use of multiple proteases. In addition, the use of focused sample-specific search databases can be used to improve the specificity of cross-linked peptide spectral matching. Application of this approach to human chromatin labeled in live cells recapitulated known and revealed new protein interactions of nucleosomes and other chromatin-associated complexes in situ. This optimized approach for mapping native protein interactions should be useful for a wide range of biological problems.

Targeting One Carbon Metabolism with an Antimetabolite Disrupts Pyrimidine Homeostasis and Induces Nucleotide Overflow

Antimetabolites that affect nucleotide metabolism are frontline chemotherapy agents in several cancers and often successfully target one carbon metabolism. However, the precise mechanisms and resulting determinants of their therapeutic value are unknown. We show that 5-fluorouracil (5-FU), a commonly used antimetabolite therapeutic with varying efficacy, induces specific alterations to nucleotide metabolism by disrupting pyrimidine homeostasis. An integrative metabolomics analysis of the cellular response to 5-FU reveals intracellular uracil accumulation, whereas deoxyuridine levels exhibited increased flux into the extracellular space, resulting in an induction of overflow metabolism. Subsequent analysis from mice bearing colorectal tumors treated with 5-FU show specific secretion of metabolites in tumor-bearing mice into serum that results from alterations in nucleotide flux and reduction in overflow metabolism. Together, these findings identify a determinant of an antimetabolite response that may be exploited to more precisely define the tumors that could respond to targeting cancer metabolism.

Extraction parameters for metabolomics from cultured cells

The successful extraction of metabolites is a critical step in metabolite profiling. By optimizing metabolite extraction, the range and quantitative capacity of metabolomics studies can be improved. We considered eight separate extraction protocols for the preparation of a metabolite extract from cultured mammalian cells. Parameters considered included temperature, pH, and cell washing before extraction. The effects on metabolite recovery were studied using a liquid chromatography high-resolution mass spectrometry (LC-HRMS) platform that measures metabolites of diverse chemical classes, including amino acids, lipids, and sugar derivatives. The temperature considered during the extraction or the presence of formic acid, a commonly used additive, was shown to have minimal effects on the measured ion intensities of metabolites. However, washing of samples before metabolite extraction, whether with water or phosphate-buffered saline, exhibited dramatic effects on measured intensities of both intracellular and extracellular metabolites. Together, these findings present a systematic assessment of extraction conditions for metabolite profiling.

Quantitative determinants of aerobic glycolysis identify flux through the enzyme GAPDH as a limiting step

Aerobic glycolysis or the Warburg Effect (WE) is characterized by the increased metabolism of glucose to lactate. It remains unknown what quantitative changes to the activity of metabolism are necessary and sufficient for this phenotype. We developed a computational model of glycolysis and an integrated analysis using metabolic control analysis (MCA), metabolomics data, and statistical simulations. We identified and confirmed a novel mode of regulation specific to aerobic glycolysis where flux through GAPDH, the enzyme separating lower and upper glycolysis, is the rate-limiting step in the pathway and the levels of fructose (1,6) bisphosphate (FBP), are predictive of the rate and control points in glycolysis. Strikingly, negative flux control was found and confirmed for several steps thought to be rate-limiting in glycolysis. Together, these findings enumerate the biochemical determinants of the WE and suggest strategies for identifying the contexts in which agents that target glycolysis might be most effective.

DOI:http://dx.doi.org/10.7554/eLife.03342.001

Cells generate energy from a sugar called glucose via a process called glycolysis. This process involves many enzymes that catalyze 10 different chemical reactions, and it essentially converts glucose step-by-step into a simpler chemical called pyruvate.

Pyruvate is then normally transported into structures within the cell called mitochondria, where it is further broken down using oxygen to release more energy. However, in cells that are rapidly dividing, pyruvate is converted into another chemical called lactate—which releases energy more quickly, but releases less energy overall. Cancer cells often convert most of their glucose into lactate, rather than breaking down pyruvate in their mitochondria: an observation known as the ‘Warburg effect’. And while many factors affect how a cell releases energy from pyruvate, it remains unclear what regulates which of these biochemical processes is most common in a living cell.

In this study, Shestov et al. have developed a computational model for the process of glycolysis and used this to investigate the causes of the Warburg Effect. The model was based on the known characteristics of the enzymes and chemical reactions involved at each step. It predicted that the activity of the enzyme called GAPDH, which carries out the sixth step in glycolysis, in many cases affects how much lactate is produced. This suggests that this enzyme represents a bottleneck in the pathway.

Next, Shestov et al. performed experiments where they used drugs to block different stages of the glycolysis pathway, and confirmed that the GAPDH enzyme is important for regulating this pathway in living cancer cells too. In these treated cells, the levels of a chemical called fructose-1,6-biphosphate (which is made in a step in the pathway between glucose and pyruvate) were either very high or very low. Shestov et al. proposed that the flow of chemicals through the glycolysis pathway is controlled by the GAPDH enzyme when the chemicals used by the enzymes upstream of GAPDH in the pathway (which includes fructose-1,6-biphosphate) are plentiful. However, if these chemicals are limited, other enzymes that are involved in earlier steps of the pathway regulate the process instead.

The findings of Shestov et al. reveal that the regulation of glycolysis is more complex than previously thought, and is also very different when cells are undergoing the Warburg Effect. In the future, these findings might help to identify the types of cancer that could be effectively treated using drugs that target the glycolysis process, which are currently being tested in pre-clinical studies.

DOI:http://dx.doi.org/10.7554/eLife.03342.002

A strategy for sensitive, large scale quantitative metabolomics

Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting factors, such as labor intensive sample preparations, low detection limits, slow scan speeds, intensive method optimization for each metabolite, and the inability to measure both positively and negatively charged ions in single experiments. Therefore, a novel metabolomics protocol could advance metabolomics studies. Amide-based hydrophilic chromatography enables polar metabolite analysis without any chemical derivatization. High resolution MS using the Q-Exactive (QE-MS) has improved ion optics, increased scan speeds (256 msec at resolution 70,000), and has the capability of carrying out positive/negative switching. Using a cold methanol extraction strategy, and coupling an amide column with QE-MS enables robust detection of 168 targeted polar metabolites and thousands of additional features simultaneously.  Data processing is carried out with commercially available software in a highly efficient way, and unknown features extracted from the mass spectra can be queried in databases.

Development and quantitative evaluation of a high-resolution metabolomics technology

Recent advances in mass spectrometry have allowed for unprecedented characterization of human metabolism and its contribution to disease. Despite these advances, limitations in metabolomics technology remain. Here, we describe a metabolomics strategy that consolidates several recent improvements in mass spectrometry technology. The platform involves a high-resolution Orbitrap mass spectrometer coupled to faster scanning speeds, allowing for polarity switching and improved ion optics resulting in enhanced sensitivity. When coupled to HILIC chromatography, we are able to quantify over 339 metabolites from an extract of HCT8 cells with a linear range of over 4 orders of magnitude in a single chromatographic run. These metabolites include diverse chemical classes ranging from amino acids to polar lipids. In addition, we also detect over 3000 additional potential metabolites present in mammalian cells. We applied this platform to characterize the metabolome of eight colorectal cancer cell lines and observed both commonalities and heterogeneities across their metabolic profiles when cells are grown in identical conditions. Together these results demonstrate that simultaneous profiling and quantitation of the human metabolome is feasible.