Advances in electron microscopy have provided unprecedented access to the structural characterization of large, flexible and heterogeneous complexes. Until recently, cryo-electron microscopy (cryo-EM) has been applied to understand molecular organization in either highly purified, isolated biomolecules or in situ. An emerging field is developing, bridging the gap between the two approaches, and focuses on studying molecular organization in native cell extracts. This field has demonstrated its potential by resolving the structure of fungal fatty acid synthase (FAS) at 4.7 Å [Fourier shell correlation (FSC) = 0.143]; FAS was not only less than 50% enriched, but also retained higher-order binders, previously unknown. Although controversial in the sense that the lysis step might introduce artifacts, cell extracts preserve aspects of cellular function. In addition, cell extracts are accessible, besides cryo-EM, to modern proteomic methods, chemical cross-linking, network biology and biophysical modeling. We expect that automation in imaging cell extracts, along with the integration of molecular/cell biology approaches, will provide remarkable achievements in the study of closer-to-life biomolecular states of pronounced biotechnological and medical importance. Such steps will, eventually, bring us a step closer to the biophysical description of cellular processes in an integrative, holistic approach.
Introduction: why high resolution?
High-resolution characterization is essential to understand function and provides access to chemical tools for exploiting the molecule of interest in a medical or biotechnological manner. The atomic resolution of biomolecules benefits the understanding of the physical-chemical basis of life processes, such as DNA replication, transcription, translation, enzymatic catalysis, folding, biomolecular recognition and aggregation, achievements that, occasionally, deserved the Nobel Prize (Supplementary Table 1).
To derive high-resolution structures, breakthroughs in biophysical methods that are employed to attain them have also been recognized by several Nobel Prize awards (Supplementary Table 1). In detail, high-resolution structures of biomolecules are attainable using X-ray diffraction [e.g. crystallography (Kendrew et al., 1958) or X-ray free electron lasers (Chapman et al., 2011)], nuclear magnetic resonance (NMR) spectroscopy [solution (Kaptein et al., 1985; Williamson et al., 1985; Kline et al., 1988) and solid-state NMR (Castellani et al., 2002)], cryo-electron microscopy (cryo-EM) [electron diffraction (ED; Henderson et al., 1990), MicroED (Shi et al., 2013) and single-particle analysis (Zhang et al., 2008; Zivanov et al., 2018)], and in extraordinary cases, cryo-electron tomography (cryo-ET) followed by subtomogram averaging (Schur et al., 2016; Turonova et al., 2017; Himes and Zhang, 2018).
These approaches benefit from advances in computational structural biology (Levitt, 2001), pioneered by Karplus (McCammon et al., 1977), van Gunsteren (van Gunsteren and Berendsen, 1977), Levitt (Levitt and Lifson, 1969), Warshel (Warshel and Levitt, 1976), Chothia and Janin (Chothia and Janin, 1975). Computational structural biology aims to provide hypotheses and predictions at the molecular level and/or supplement data with physics- and evolutionary-based calculations.
High-resolution structural methods have different philosophies
High-resolution structural methods often have heterogeneous philosophies: For example, X-ray crystallography reports structures of highly purified, concentrated biomolecules and provides insights into their function. X-ray crystallography acts as the primary method to optimize function using structure-based drug design. Moreover, it is no surprise that, after 100 years of crystallography, currently, nine out of 10 biomolecular structures at high resolution stem from X-ray crystallography (www.pdb.org). Solution NMR spectroscopy, although considered a high-resolution method after the works of the groups of Wüthrich (Williamson et al., 1985) and Kaptein (Kaptein et al., 1985), is currently occupied with resolving biomolecular dynamics, kinetics and excited states. Similar to crystallography, samples must be highly pure to be studied, but, contrary to X-ray crystallography, where samples are analyzed in their crystal-like state, in NMR, samples may be studied at room temperature while being active. However, samples of increased complexity are currently difficult to study using NMR, a field that solid-state NMR is concealing (Weingarth and Baldus, 2013).
Electron microscopy has traditionally been a structural method for the description of in situ structures, previously unthinkable to reach a high resolution. However, advances in cryo-EM (Frank, 2017; Raunser, 2017), such as direct electron detectors to increase the signal-to-noise ratio in electron micrographs (McMullan et al., 2014) and automation in data acquisition on the microscopes (Carragher et al., 2000; Mastronarde, 2005) and in image processing (Hohn et al., 2007; Scheres, 2012; de la Rosa-Trevin et al., 2013), led to the resolution revolution as portrayed by Kühlbrandt (2014). Nowadays, structures of biomolecules regularly reach near-atomic resolution and it seems that methodological limitations are being surpassed [e.g. sample size (Khoshouei et al., 2017) and radiation damage (Allegretti et al., 2014; Grant and Grigorieff, 2015)]. The field is still in active development but, often, resolution is not uniform, or the interpretation of electron optical density maps is difficult due to decreased local resolution (Neumann et al., 2018). Fluctuations in local resolution are observed in cryo-EM maps, and the origins are complex, including biomolecular dynamics, biochemical/biophysical heterogeneity or single-particle alignment inaccuracies. Standard procedures in the field have not been settled; data collection practices, image processing strategies and resolution estimation theories are under active discussion (Henderson et al., 2012; van Heel and Schatz, 2017). The current philosophy of cryo-EM resembles that of X-ray crystallography, in a sense that samples are purified to homogeneity, being as stable as possible to trap a low-energy state.
Last but not least, cryo-ET followed by subtomogram averaging is again entailing a different philosophy with few laboratories reaching atomic resolution (Schur et al., 2016; Turonova et al., 2017; Himes and Zhang, 2018), previously also thought unattainable due to methodological limitations which are now addressed [e.g. data acquisition tilt schemes (Hagen et al., 2017), contrast transfer function correction (Kunz and Frangakis, 2017) etc.]. Despite few examples, cryo-ET describes in situ processes at the highest possible resolution (Mahamid et al., 2016) combining data from auxiliary biochemical and biophysical methods (Beck and Baumeister, 2016; Beck et al., 2018). This is exemplified by the structure of the nuclear pore complex (NPC), which within a few years has undergone its own revolution (von Appen and Beck, 2016), from low resolutions (~60 Å) to those very close to identify and localize all structural proteins of the NPC unambiguously (~20 Å) (Bui et al., 2013; Stuwe et al., 2015; von Appen et al., 2015; Kosinski et al., 2016; Lin et al., 2016). This was achieved with state-of-the-art cryo-ET, proteomics, crystallography, computational modeling and striking integrative approaches to explain protein-protein interactions (Kosinski et al., 2016), sometimes directly from structures within cells (Mosalaganti et al., 2018).
The ‘molecular identity gap’ prohibits deeper understanding of cellular organization
Samples that are studied using the aforementioned methods are either biomolecules purified to homogeneity or cells/organelles that are deposited on a grid to be subsequently structurally analyzed. The advantage of homogeneous, highly pure samples is that they have higher probabilities to reach near-atomic resolution, and therefore, have access to subsequent chemical tools. However, molecules are purified and are studied outside the cellular context, implying that their overall architecture is just a snapshot, not necessarily of what happens inside the cell. On the other hand, in situ methods study the architecture of molecular species in cells; yet, if the identity of the biomolecules is not known a priori, it is difficult to characterize unassigned electron optical densities of biomolecules in any reconstruction from in situ maps. Unfortunately, protein identification using mass spectrometry (MS) has not reached single-cell proteomics to categorize molecules in situ (Beck and Baumeister, 2016), although advances in this field are being made (Budnik et al., 2018). It would not be a surprise if, in the years to come, advances in analytical chemistry will allow protein identification from single-cell samples or even directly from the cryo-EM grids. Therefore, currently, an obvious gap in understanding cellular architecture exists with the current structural methods. This gap can be termed as the ‘molecular identity gap’: Molecules in purified samples are unambiguously determined, but are outside the cellular milieu. Conversely, molecules in situ, although present in a closer-to-life biomolecular state, can only be identified if already known, and very rarely reach a high resolution (Figure 1).
Bridging the molecular identity gap by studying cell extracts
This ‘molecular identity gap’ can be bridged with structural biology methods aiming to study biomolecules that are in a quasi-purified state (Figure 1); this means biomolecules that are present in highly heterogeneous mixtures, for example cell extracts. Cell extracts carry the advantage of being in a closer-to-life state as compared to homogeneous biomolecules (Kastritis et al., 2017; Kastritis and Gavin, 2018). This is because they retain interactions that would have been completely removed in downstream purification protocols, where high purity is desirable for structure elucidation with traditional methods. In addition, advances in analytical methods have gone hand in hand with the study of native cell extracts: For example, the proteomic identification of protein complexes was extremely challenging in the recent past (Gavin et al., 2002), but is now common practice, e.g. with theories regarding the evolution of protein complexes (Wan et al., 2015). This is in part due to the algorithmic development for quantitative proteomics [e.g. open-source (Rost et al., 2016)] and increased sensitivity of mass spectrometers (Eliuk and Makarov, 2015). Cross-linking mass spectrometry (XL-MS) methods have moved from studying purified samples (Sinz, 2003; Rappsilber, 2011) to characterizing samples of increased complexity (O’Reilly and Rappsilber, 2018; Sinz, 2018); Nowadays, XL-MS recovers thousands of biomolecular interfaces in cell extracts (Kastritis et al., 2017), directly in purified organelles (Liu et al., 2018), or even in vivo (Chavez et al., 2018). Recent advances in XL-MS technology (Liu et al., 2015; Iacobucci et al., 2018) are expected to increase the discovery of cross-links in heterogeneous samples. Therefore, it is obvious that cell extracts retain certain advantages for biochemical manipulation, which are not available when studying intact cells. Cell extracts have another advantage: Computational structural biology algorithms can be applied to understand the structure of protein-protein interactions discovered with proteomics (Kastritis et al., 2017). In addition, network biology characterizes the architecture of higher-order interaction networks that reside within those extracts (Havugimana et al., 2012). The first protocols that combined proteomic identification in cell extracts with direct protein quantification have been developed (Havugimana et al., 2012) and sophisticated network biology is applied to understand the interconnectivity of the proteome (Kastritis et al., 2017). This led to the understanding of novel architectures of protein complexes and the beginning of the validation of interconnected metabolic pathways (Wan et al., 2015), initially identified in a global level using affinity purification coupled to mass spectrometry (AP-MS) by Gavin (Gavin et al., 2002; Gavin et al., 2006).
Methods to assign identities to protein complexes observed in native cell extracts
Visualizing the architecture of organelle structures within cell extracts is not novel – the correlation of biochemistry with electron microscopy dates back to the 1950s with the works of Nobel Prize winners Palade, Claude and de Duve (Hogeboom et al., 1948; Claude, 1950; Baudhuin et al., 1965). Works in the past have reported imaging of protein complexes in cell extracts with electron microscopes (Haselkorn et al., 1965; Oudet et al., 1975; Mowbray and Moses, 1976). Nevertheless, only recently, comprehensive low-resolution imaging of biomolecular complexes in native cell extracts was achieved (Kastritis et al., 2017). The authors fractionated cell extracts from a thermophilic fungus (Chaetomium thermophilum) and subsequently performed large-scale electron microscopy imaging of all fractions (Figure 2A–C). These fractions were amenable to proteomic identification and electron microscopy because the separation method that was applied (Kristensen et al., 2012) allowed the elution of large molecular weight complexes, which are rendered visible under the electron microscope. Observation of proteinaceous material in native cell extracts allowed access to large-scale identification and visualization of protein complexes and their interconnectivity.
Electron microscopy without proteomic identification of the cellular extract cannot provide characterization of the visualized biomolecular assembly, a problem described previously and encountered in cryo-ET of organelles or cells. To address this, the authors developed a method to proteomically identify the shapes of the biomolecules (structural signatures) observed under the electron microscope (Kastritis et al., 2017): In brief, the abundance of proteins in each fraction is calculated using proteomic quantitation, and simultaneously, in the same fractions, the frequency of appearance of each structural signature is derived using large-scale electron microscopic imaging (Figure 2C). By correlating these two quantities, the identification of structural signatures is possible, at least for those that are highly abundant and elute over four or more native fractions. Another way to identify the structural signatures within native cell extracts is further orthogonal purification of each fraction (Figure 2D). It is expected that if the complex has not aggregated or changed the conformation, it can be visualized in the subsequent purification step, and therefore, identified in a fraction again using MS, but in a much less complex environment. This would mean a less ambiguous identification and less relying on statistics; a disadvantage could well be, however, that scaffolds or binders might dissociate, and therefore, the identification of binders will not be possible in downstream purification protocols.
Low-resolution 3D reconstructions of proteins and protein complexes in native cell extracts come within reach
Image processing of heterogeneous specimens and even 3D reconstructions of heterogeneous mixtures of biomolecules are possible (Takagi et al., 2003). Native cell extracts are accessible to image processing both at low and high resolutions (Kastritis et al., 2017 and Figure 3A,B). Currently, more studies are validating and expanding image processing of cell extracts, either by calculating multiple reconstructions from a single, stained fraction (Verbeke et al., 2018) or by using the stained cell extract of single cells to produce low-resolution 3D reconstructions of ribosomes (Yi et al., 2018). It is expected that the identification of structural states of native protein complexes is within reach and the application of similar protocols used to derive class averages from cellular fractions will lead to an overview of cellular organization. A challenge faced by image processing algorithms is the fact that many protein complexes exist simultaneously in the sample (Figure 3A).
Bayesian approaches (Sigworth, 1998), further applied by Scheres for user-friendly, semi-automated cryo-EM data analysis (Scheres, 2012), can outstandingly distinguish complexes of different states. Bayesian approaches may independently reconstruct structural signatures in three dimensions, therefore solving the heterogeneity problem, not only at the single-molecule level, but also at the level of discriminating and reconstructing simultaneously distinct protein complexes of high abundance (Figure 3A and Kastritis et al., 2017). This was demonstrated by the simultaneous reconstruction of the human ribosome and proteasome, present in the same cellular fraction after the application of a negative stain (Verbeke et al., 2018).
High-resolution structure determination from cell extracts: the breakthrough of fatty acid synthase (FAS)
Cells and cell extracts are accessible to high-resolution data acquisition (Luchinat and Banci, 2017), especially using NMR methods (Selenko et al., 2008; Theillet et al., 2013). Even structure determination is feasible with in-cell NMR (Inomata et al., 2009). Still, in the case of Inomata et al. (2009), ubiquitin was mutated to preserve a monomeric state, ideal for NMR. In addition, most proteins are expressed in micromolar or millimolar concentrations, rendering the cell in a state of single-protein overexpression.
Cryo-EM provides an appealing alternative for high-resolution analysis of native cell extracts. This is because (a) molecules are not overexpressed, but are visualized in their native abundances; (b) cells are not grown in method-specific media; and (c) biomolecules can be visualized without a priori knowledge of what is being imaged. Striking examples include purified Tau filaments from human Alzheimer’s disease brain and subsequent near-atomic description of their structural heterogeneity (Fitzpatrick et al., 2017) and a thermophilic eukaryotic FAS from cell extracts (Kastritis et al., 2017). In the latter example, FAS was present in a native cellular fraction with less than 50% enrichment. After imaging the fraction at the electron microscope, image processing was applied. Using 3933 single particles of FAS, a reconstruction at near-atomic resolution was achieved (Kastritis et al., 2017 and Figure 4). The reconstruction showed superior features as compared to already published cryo-EM maps of FAS from other species (Gipson et al., 2010; Boehringer et al., 2013; Fischer et al., 2015). For example, the cap of the molecule was clearly resolved, although in previous cryo-EM reconstructions it was absent. In addition, the structure was derived with very few single particles, illustrating the strength of C. thermophilum as a model system for high-resolution structure determination. Other structures of FAS, recently resolved with similar technology, reach higher resolutions (D’Imprima et al., 2018; Elad et al., 2018) but use a comparatively much higher number of single particles not only for the final reconstruction (Figure 4), but also for every single step in image processing. On the other hand, careful interpretation of the compared cryo-EM maps of FAS is required; the advantages of studying C. thermophilum FAS in cellular extracts should be ultimately compared to C. thermophilum FAS after purification to homogeneity. This is because C. thermophilum FAS has intrinsic stability and rigidity and has been acquired with direct electron detection, while other FAS structures do not have similar features and/or have been acquired with older detection technologies.
Chaetomium thermophilum is a promising system for structural biology (Amlacher et al., 2011). Its application has been successful in the recombinant expression of C. thermophilum nucleoporins and the subsequent structural determination by X-ray crystallography (Lin et al., 2016). Chaetomium thermophilum has been a system of extensive study in the field of NPC (Amlacher et al., 2011) but is currently expanding as a model system for structure determination due to the aforementioned encouraging results (Kastritis et al., 2017). Recently, genetic modification of the fungus was pioneered in the Hurt laboratory (Kellner et al., 2016), opening doors to a genetic toolkit for structural biotechnology using a thermophilic source.
Cell lysis as the major limitation in the study of cell extracts
Study of cell extracts and subsequent application of purification protocols have been a matter of debate since the beginnings of centrifugation applied to biological samples (De Duve and Berthet, 1954). Arguments for distorting the natural cellular state are plenty, because, certainly, lysis of the cells leads to an irreversible thermodynamic state of its contents, which is unlikely to be the one biomolecules attained before lysis. A large volume of aggregates must be removed, e.g. by ultracentrifugation, therefore, in principle, losing high amounts of cellular material. In addition, harsh centrifugation steps dramatically increase dissociation events of fragile and/or transient complexes. It is known, for example, that sedimentation of pyruvate dehydrogenase complexes (PDC) must be gentle, else dissociation of the complex occurs, manifested by diminished activity in homogeneous fractions as compared to native cell extracts (Pettit and Reed, 1982). Another issue connected to lysis is that excluded volume effects already present in the cellular environment are dramatically reduced after lysis. Consequently, biomolecular interactions present in the cell due to those effects are simply lost. Any dilution that might occur downstream in the handling of the homogenate would further lead to dissociation events. Additionally, membrane-bound or membrane material is discarded, and, until now, only the soluble part of cell extracts is investigated. This also affects the recovered structural states of biomolecules in the cell extracts, because molecules that function in a dynamic exchange between membrane-bound and membrane-free environments have under-represented biological states. Lysis could even lead to structural distortions of cellular material: It was shown that mitochondria from yeast, while in situ have been observed to acquire an elongated shape, when isolated and purified after sucrose gradient centrifugation, appear to be circular (Daum et al., 2013). This dramatic change in shape could also happen at a lower-order molecular level, such as in the case of biomolecular assemblies. Therefore, lysis may further contribute to alterations in protein structure. An opposite effect might also happen during lysis: Instead of dissociating biomolecular complexes, association of non-specific binders could occur, that would otherwise just be in close vicinity inside the cell. Therefore, interpretation of higher-order assemblies of biomolecular complexes present in cell extracts could partially stem from the binding of non-specific interactions that happened to co-exist in the same cellular micro-compartment.
All the aforementioned concerns are rational and, unfortunately, difficult to be circumvented when applying any biochemical method. Until a combination of structural and molecular biology methods allows the unambiguous identification and high-resolution structure determination of protein complexes directly from cells, the study of cellular organization utilizing cell extracts is the closer-to-native biochemical approach that is in our research toolkit. One could in principle argue that the aforementioned phenomena are reduced after (a) various separation methods to be applied that lead to the same results; (b) cross-linking experiments that would stabilize transient biomolecular interactions before cell lysis (a counter-argument could be that XL-MS alters the structure, leading the biomolecules to different thermodynamic states); (c) utilization of thermostable organisms to minimize dissociation of biomolecular assembly; (d) direct inspection of the material in the cell extract with electron microscopy, confirming that aggregates or non-specific interactions are minimized; and (e) measuring reproducible protein abundance in cell extracts in different experiments to partially avoid non-specific interactions. Overall, technical and biological reproducibility is essential to partially trouble-shoot the aforementioned concerns. Of course, validation is vital to understand the relation to in-cell phenomena, either with functional assays or with complementary in-cell visualization/characterization methods (e.g. super-resolution microscopy and in-cell NMR).
Native cell extracts retain principles of cellular function
The aforementioned concerns are frequently addressed by the proven value of cell extracts as model systems to study function. Breakthrough studies by Nirenberg and Matthaei (1961), who used cell extracts to translate poly-uracyl RNA sequences, led to the discovery of polypeptide synthesis. Cell extracts, therefore, played a pivotal role in deciphering the genetic code. Recently, biotechnological applications of translation have led to the employment of various types of cell extracts for protein production, such as the usage of extracts from rabbit reticulocytes, Escherichia coli, wheat germ and insect cells. Nowadays, yields exceed grams of protein per liter of reaction volume (Caschera and Noireaux, 2014). Another example is homogenates from Xenopus eggs, which were used to understand DNA damage and repair (Cupello et al., 2016). Xenopus egg extracts contain all molecular factors that are required to perform DNA repair outside a cell, using mechanisms conserved in humans (Hoogenboom et al., 2017). Other applications of cell extracts include, and are not limited to, metabolic manipulation (Hodgman and Jewett, 2012), e.g. the optimal production of adenosine triphosphate (ATP) (Calhoun and Swartz, 2005), unnatural amino acid incorporation (Noren et al., 1989) and, in particular, manipulation for structural biology studies (Kigawa et al., 1999).
Overall, cell extracts, also termed as cell-free systems when it comes to biotechnological approaches, have various advantages, not only to study cellular function but also to be used for applied research as compared to their cellular counterparts (Zemella et al., 2015). Although they are susceptible to degradation outside their host organism, they have, in comparison to their cellular counterparts, (a) higher product yields that are accomplished by minimizing by-products; (b) the ability to implement biological reactions that living systems or chemical catalysts cannot implement, or if they can, the efficiency with cell-free systems is increased; (c) higher reaction rates, e.g. enzymatic fuel cells have higher power outputs (Zhu et al., 2014); (d) higher tolerance to toxic compounds; and (e) broad reaction conditions, such as high temperature, low pH and tolerance when organic solvents or ionic liquids are present, and therefore, can be biochemically conditioned in a broader spectrum.
Cryo-EM of native cell extracts uncovers higher-order assemblies
Previously, the structure of FAS from native cell extracts was described and was found bound to various MDa-complexes of unknown identities (Kastritis et al., 2017). Using proteomics and XL-MS, identification of a binder of FAS was achieved, which was a fungal-specific carboxylase, forming an interaction interface with FAS. This interface was not random, as the binding site was localized at the entrance/exit tunnel of the acyl chain, and corroborating XL-MS data also pointed to the location that was identified with cryo-EM (Kastritis et al., 2017). Higher-order states are visible in cryo-EM micrographs of various fractions (Figure 5), and connections of biomolecules with electron dense material are apparent. This material is of unknown origin and we hypothesize it to have a structural role, e.g. maintaining the structural integrity of the higher-order complex. Higher-order organization within cell extracts was never observed before at such resolution, and we suppose that the combination of cryo-EM with -omics techniques will provide additional insights into scaffolds that organize biomolecular complexes. It is attractive to assume that higher-order assemblies are prearranged not only on membranes or cytoskeletal elements, but also on flexible biomacromolecules, such as disordered proteins and/or RNA. Of course, structural characterization of flexible binders is still outside our reach. Currently, the only method that can resolve conformational states of disordered proteins is NMR, as shown by the striking example of a complex between a chaperone and a disordered protein by the Kalodimos group (Huang et al., 2016). These systems are currently challenging to model and they will remain at much lower resolution as compared to their structured counterparts in cryo-EM of cell extracts.
Present limitations and future goals in the study of cell extracts at high resolutions
Structures of less abundant molecular species in cell extracts are currently outside reach
It is expected that abundant protein complexes will be amenable to high-resolution structure determination in native cell extracts, such as FAS, the ribosome, proteasome, glycolytic enzymes, etc. In fact, during the revisions of our manuscript, using a microfluidic approach for protein isolation, the structure of the 20S proteasome from 1 μl of the HeLa lysate was determined at 3.5 Å resolution (Schmidli et al., 2019). However, advances in hardware and software automation will allow resolving structures of less abundant biomolecular complexes. Two recent advances in cryo-EM highlight this fact. One example, regarding hardware advances, is the Volta phase plate (Danev et al., 2014). We envision that in its current or more advanced form in the future, it can greatly increase the contrast of electron microscopy images to an extent that even smaller biomolecules will be reliably identified at the single-particle level. This might be crucial to (a) understand higher-order structure in cell extracts by acquiring less data and (b) computationally simplify the sorting of highly heterogeneous specimens. The other examples, regarding software advances, are deep-learning approaches, particularly in single-particle picking (Wagner et al., 2018). Recent and future efforts to apply sophisticated image recognition algorithms to highly heterogeneous samples will further support particle assignment and will aid the structural characterization of multiple different biomolecules from a single sample. Considering biochemical preparation protocols, fractionation of different organelles is another idea to enrich for organelle-specific pathways in the extracts. These would have the advantage of being simpler to study with cryo-EM and, in principle, minimize non-specific interactions with biomolecules from other compartments.
Still, very low abundant complexes are unlikely to be resolved or annotated. For this reason, molecular biology methods and genetic manipulation of the model organisms are essential to monitor assembly principles of biomolecules of interest using, e.g. gold tags to be visualized in electron microscopy or fluorescent tags to be visualized with light microscopy. For example, cryo-correlative light-electron microscopy (cryo-CLEM) on cellular fractions could theoretically image rare binding events. Subsequent cryo-ET may provide electron density maps of these complexes at medium resolution, and combination with computational modeling of rare biomolecular assemblies could decipher the higher-order organization of low abundant complexes.
Molecular complexity limits the physical-chemical interpretation with computational structural biology
Currently, combination of methods with cryo-EM of cell extracts can resolve the interfaces of biomolecular interactions such as XL-MS coupled to flexible protein docking using cryo-EM density maps as restraints. Programs that could, in principle, perform such modeling include IMP (Webb et al., 2018) for the coarse-grained description of biomolecular assemblies, and HADDOCK for atomic modeling (van Zundert et al., 2016). Major progress in software to handle heterogeneous data is well reflected in the ongoing development of HADDOCK, a docking program that utilizes the Crystallography and NMR System (Brunger et al., 1998) as its computational engine. Although HADDOCK was conceived for data integration (Dominguez et al., 2003), it only included mutagenesis and NMR data to guide the modeling procedure. After 15 years of development, HADDOCK emerged into an integrative modeling suite (van Zundert et al., 2016), dealing with data derived from various methods, e.g. cryo-EM (van Zundert et al., 2015), co-evolution (Hopf et al., 2014), chemical XL-MS (Kastritis et al., 2017), ion mobility MS (IMS-MS) and small-angle X-ray scattering (SAXS) (Karaca and Bonvin, 2013). Large macromolecular complexes (Karaca et al., 2017) or membrane complexes (Koukos et al., 2018) can be modeled using HADDOCK at atomic resolution, while being able to handle various types of biomolecules (small molecules, proteins and peptides, nucleic acids or lipids). Such a variety of data is interpretable as distance restraints (Bonvin et al., 2018) and, in addition, HADDOCK can be used in combination with other high-end modeling software (Orban-Nemeth et al., 2018).
Prediction of the binding affinity of higher-order assemblies present in cell extracts
Computational algorithms that deal with a variety of data will become indispensable for studying architecture of cell extracts. Especially HADDOCK has a rigorous scoring function (Vangone et al., 2017), based on physical-chemical principles. The scoring function is so robust that it can be used to predict macromolecular binding affinity in a qualitative manner (Kastritis and Bonvin, 2010). In addition, HADDOCK scoring may describe the binding strength of protein-protein complex inhibitors within experimental uncertainty (Kastritis et al., 2014a).
In the future, HADDOCK can even serve as a tool for structure-based binding affinity prediction of captured transient interfaces within cell extracts. Note that most of these interfaces remain unknown because they are simply lost during conventional purification methods. Therefore, understanding the physical basis of their recognition would open the door to the characterization of their physical chemistry. This is highly relevant considering that genetic disorders caused by enzymopathies occur due to single-point mutations on enzymes. Interestingly, ~30% of those mutations reside far from their active site (Gao et al., 2015), a finding which correlates well with the dependence of binding affinity on the physical-chemical properties of the non-interacting surface (Kastritis et al., 2014b; Visscher et al., 2015). Therefore, an appealing idea is that these mutations could be rationalized by structural errors in the higher-order assembly of biomolecular complexes, and can be captured within cell extracts.
Nevertheless, progress in biomolecular modeling is still needed, as higher-order assemblies include a high number of atoms, rendering programs that model biomolecular architectures at atomic resolution inefficient in performing analytical calculations. Therefore, a possible combination between coarse-grained and fine-grained force fields to tackle such complicated refinement challenges must come within reach. Advances in force field development should be accompanied with innovations in quantum computing (O’Malley et al., 2016) that are expected to decrease simulation times and increase simulation accuracy.
Native cell extracts as open systems for biophysical studies of biomolecular stability
It is conceivable that cell extracts can be probed using the physical-chemical changes in their buffer environment. Together with computation of energetics of the interfaces present in cell extracts, changes in buffer conditions can monitor the assembly/disassembly principles of biomolecules. In addition, cell extracts may reflect growth conditions of their host organisms and therefore, changes in biomolecular assemblies after culturing in different growth media can be probed. Molecular organization hypotheses can directly be tested, e.g. by treating cell extracts with enzymes or metabolites that are expected to affect higher-order structural organization. Such probing can additionally build up assumptions regarding the overall physical-chemical and biomolecular nature of the cell extract under study. Synthetic biology approaches may also be applied, for example, probing the interaction of cell extracts with additional scaffolds or crowding agents, such as membranes or chemicals.
The ‘fathers’ of biochemistry would not have predicted that a time would come to structurally probe the biomolecular content of cell extracts at high resolutions. Overall, cell extracts hold promise to fathom a higher level of detail related to the structural organization of cellular processes. Keeping in mind the limitations that biochemical lysis and subsequent treatments impose, cell extracts cannot fully grasp the complex biology of an organism. Despite that, their structure is closer to native as compared to all other samples used for high-resolution structural analysis.
Toward this goal, structural biology methods have great potential, especially cryo-EM, which has proved its capability to study cell extracts and resolve structures from cellular fractions at near-atomic resolutions. In parallel, proteomic methods, and XL-MS in particular, are being optimized to handle such samples, therefore offering valuable data to understand their biomolecular content and associated biomolecules. Network biology and computational structural biology are expected to provide valuable insights into the biophysics of cell extracts and resolve the interconnectivity of domains and biomolecules within. It is expected that molecular and cellular biology will critically aid in studying less abundant biomolecules within the cell extracts and together with traditional structural methods will establish the deeper understanding of cellular processes at the highest possible achievable resolution.
We are confident that, in the years to come, such transient, higher-order assemblies will be, eventually, structurally characterized with various approaches. Such understanding will consequently offer the raw material to benchmark, optimize and finally design molecules of great biotechnological and medical potential through rationalizing the molecular origins of function and disease.
Funding source: Federal Ministry for Education and Research (BMBF, ZIK program)
Award Identifier / Grant number: 02Z22HN23 (to P.L.K.)
Funding source: European Regional Development Fund
Award Identifier / Grant number: EFRE: ZS/2016/04/78115 (to P.L.K.)
Funding statement: This work was supported by the Federal Ministry for Education and Research (BMBF, ZIK program) [grant number 02Z22HN23 (to P.L.K.)]; the European Regional Development Funds for Saxony-Anhalt [grant number EFRE: ZS/2016/04/78115 (to P.L.K.)] and the Martin Luther University Halle-Wittenberg. The authors acknowledge EMBL for collecting images at the FEI Tecnai Polara microscope. We thank Dr. Matteo Allegretti (EMBL Heidelberg), Dr. Aggelos Banos (BRFAA, Athens), Dr. Marta Fratini (DKFZ, Heidelberg), Dr. Thodoris Karamanos (NIH, Bethesda) and Dr. João Rodrigues (Structural Biology Department, Stanford University) for the critical reading of the manuscript.
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©2019 Fotis L. Kyrilis et al., published by De Gruyter, Berlin/Boston
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