Detecting protein communities in native cell extracts by machine learning : a structural biologist’s perspective

Native cell extracts hold great promise for understanding the molecular structure of ordered biological systems at high resolution. This is because higher-order biomolecular interactions, dubbed as protein communities, may be retained in their (near-)native state, in contrast to extensively purifying or artificially overexpressing the proteins of interest. The distinct machine-learning approaches are applied to discover protein–protein interactions within cell extracts, reconstruct dedicated biological networks, and report on protein community members from various organisms. Their validation is also important, e.g., by the cross-linking mass spectrometry or cell biology methods. In addition, the cell extracts are amenable to structural analysis by cryo-electron microscopy (cryo-EM), but due to their inherent complexity, sorting structural signatures of protein communities derived by cryo-EM comprises a formidable task. The application of image-processing workflows inspired by machine-learning techniques would provide improvements in distinguishing structural signatures, correlating proteomic and network data to structural signatures and subsequently reconstructed cryo-EM maps, and, ultimately, characterizing unidentified protein communities at high resolution. In this review article, we summarize recent literature in detecting protein communities from native cell extracts and identify the remaining challenges and opportunities. We argue that the progress in, and the integration of, machine learning, cryo-EM, and complementary structural proteomics approaches would provide the basis for a multi-scale molecular description of protein communities within native cell extracts.Publikationsfonds ML

Cryo-EM of a heterogeneous biochemical fraction elucidates multiple protein complexes from a multicellular thermophilic eukaryote

Biomolecular complexes and their interactions govern cellular structure and function. Understanding their architecture is a prerequisite for dissecting the cell's inner workings, but their higher-order assembly is often transient and challenging for structural analysis. Here, we performed cryo-EM on a single, highly heterogeneous biochemical fraction derived from Chaetomium thermophilum cell extracts to visualize the biomolecular content of the multicellular eukaryote. After cryo-EM single-particle image processing, results showed that a simultaneous three-dimensional structural characterization of multiple chemically diverse biomacromolecules is feasible. Namely, the thermophilic, eukaryotic complexes of (a) ATP citrate-lyase, (b) Hsp90, (c) 20S proteasome, (d) Hsp60 and (e) UDP-glucose pyrophosphorylase were characterized. In total, all five complexes have been structurally dissected in a thermophilic eukaryote in a total imaged sample area of 190.64 μm2, and two, in particular, 20S proteasome and Hsp60, exhibit side-chain resolution features. The C. thermophilum Hsp60 near-atomic model was resolved at 3.46 Å (FSC = 0.143) and shows a hinge-like conformational change of its equatorial domain, highly similar to the one previously shown for its bacterial orthologue, GroEL. This work demonstrates that cryo-EM of cell extracts will greatly accelerate the structural analysis of cellular complexes and provide unprecedented opportunities to annotate architectures of biomolecules in a holistic approach

Cryo-EM and artificial intelligence visualize endogenous protein community members

Cellular function is underlined by megadalton assemblies organizing in proximity, forming communities. Metabolons are protein communities involving metabolic pathways such as protein, fatty acid, and thioesters of coenzyme-A synthesis. Metabolons are highly heterogeneous due to their function, making their analysis particularly challenging. Here, we simultaneously characterize metabolon-embedded architectures of a 60S pre-ribosome, fatty acid synthase, and pyruvate/oxoglutarate dehydrogenase complex E2 cores de novo. Cryo-electron microscopy (cryo-EM) 3D reconstructions are resolved at 3.84–4.52 Å resolution by collecting <3,000 micrographs of a single cellular fraction. After combining cryo-EM with artificial intelligence-based atomic modeling and de novo sequence identification methods, at this resolution range, polypeptide hydrogen bonding patterns are discernible. Residing molecular components resemble their purified counterparts from other eukaryotes but also exhibit substantial conformational variation with potential functional implications. Our results propose an integrated tool, boosted by machine learning, that opens doors for structural systems biology spearheaded by cryo-EM characterization of native cell extracts

Cryo-EM snapshots of a native lysate provide structural insights into a metabolon-embedded transacetylase reaction

Found across all kingdoms of life, 2-keto acid dehydrogenase complexes possess prominent metabolic roles and form major regulatory sites. Although their component structures are known, their higher-order organization is highly heterogeneous, not only across species or tissues but also even within a single cell. Here, we report a cryo-EM structure of the fully active Chaetomium thermophilum pyruvate dehydrogenase complex (PDHc) core scaffold at 3.85 Å resolution (FSC = 0.143) from native cell extracts. By combining cryo-EM with macromolecular docking and molecular dynamics simulations, we resolve all PDHc core scaffold interfaces and dissect the residing transacetylase reaction. Electrostatics attract the lipoyl domain to the transacetylase active site and stabilize the coenzyme A, while apolar interactions position the lipoate in its binding cleft. Our results have direct implications on the structural determinants of the transacetylase reaction and the role of flexible regions in the context of the overall 10 MDa PDHc metabolon architecture.Publikationsfonds ML

Cryo-EM structure of the SEA complex

The SEA complex (SEAC) is a growth regulator that acts as a GTPase-activating protein (GAP) towards Gtr1, a Rag GTPase that relays nutrient status to the Target of Rapamycin Complex 1 (TORC1) in yeast 1 . Functionally, the SEAC has been divided into two subcomplexes: SEACIT, which has GAP activity and inhibits TORC1, and SEACAT, which regulates SEACIT 2 . This system is conserved in mammals: the GATOR complex, consisting of GATOR1 (SEACIT) and GATOR2 (SEACAT), transmits amino acid 3 and glucose 4 signals to mTORC1. Despite its importance, the structure of SEAC/GATOR, and thus molecular understanding of its function, is lacking. Here, we solve the cryo-EM structure of the native eight-subunit SEAC. The SEAC has a modular structure in which a COPII-like cage corresponding to SEACAT binds two flexible wings, which correspond to SEACIT. The wings are tethered to the core via Sea3, which forms part of both modules. The GAP mechanism of GATOR1 is conserved in SEACIT, and GAP activity is unaffected by SEACAT in vitro. In vivo, the wings are essential for recruitment of the SEAC to the vacuole, primarily via the EGO complex. Our results indicate that rather than being a direct inhibitor of SEACIT, SEACAT acts as a scaffold for the binding of TORC1 regulators.</p

2.7 Å cryo-EM structure of vitrified M. Musculus H-chain apoferritin from a compact 200 keV cryo-microscope

Here we present the structure of mouse H-chain apoferritin at 2.7 Å (FSC = 0.143) solved by single particle cryogenic electron microscopy (cryo-EM) using a 200 kV device, the Thermo Fisher Glacios®. This is a compact, two-lens illumination system with a constant power objective lens, without any energy filters or aberration correctors, often thought of as a "screening cryo-microscope". Coulomb potential maps reveal clear densities for main chain carbonyl oxygens, residue side chains (including alternative conformations) and bound solvent molecules. We used a quasi-crystallographic reciprocal space approach to fit model coordinates to the experimental cryo-EM map. We argue that the advantages offered by (a) the high electronic and mechanical stability of the microscope, (b) the high emission stability and low beam energy spread of the high brightness Field Emission Gun (X-FEG), (c) direct electron detection technology and (d) particle-based Contrast Transfer Function (CTF) refinement have contributed to achieving high resolution. Overall, we show that basic electron optical settings for automated cryo-electron microscopy imaging can be used to determine structures approaching atomic resolution

ChIP-seq analysis revealing the mH2A1.1, mH2A1.2 and mH2A2 binding patterns in MEFs and ESCs. A.

Summary and Tornado plots depicting the binding of mH2A1.1 (left panels), mH2A1.2 (middle panels) and mH2A2 (right panels), in MEFs (upper panels) and ESCs (lower panels). Signal is normalized as log2FC (IP signal/Input signal) and peaks were defined using SICER2. B. Venn diagrams depicting the mH2A individual variant targets of the 73 mH2AMET/EMT genes in MEFs and ESCs. Targets were defined using the broad peaks derived from peak-calling analysis with SICER2 and peaks were annotated to genes with GREAT tool (±10 kb from the TSS). mH2A1.1 and mH2A2 have the most targets in MEFs, whereas in ESCs mH2A1.1 is the primary variant with direct binding at the 73 mH2AMET/EMT gene loci. C. Heatmaps depicting comparative ChIPseq analysis of mH2A1.1, mH2A1.2 and mH2A2 variants bound to the 73 mH2AMET/EMT genes in MEFs and ESCs as indicated. The average mH2A binding was calculated either at the -5kb regulatory region upstream from TSS or at the gene bodies after RPKM normalization. D. Intersection of the data presented in Fig 2B and S3C Fig. Genes with direct binding of a mH2A-bearing nucleosome are depicted in yellow and genes with no significant mH2A binding are depicted in black. (TIF)</p