Search bioRxiv⌕ Search

Biology subjects

Baker, D.

Publications and source records attributed to Baker, D..

At least 199 records · Page 11Linked to original sources

Randomized gates eliminate bias in sort-seq assays

Sort-seq assays are a staple of the biological engineering toolkit, allowing researchers to profile many groups of cells based on any characteristic that can be tied to fluorescence. However, current approaches, which segregate cells into bins deterministically based on their measured fluorescence, introduce systematic bias. We describe a surprising result: one can obtain unbiased estimates by incorporating randomness into sorting. We validate this approach in simulation and experimentally, and describe extensions for both estimating group level variances and for using multi-bin sorters.

bioengineering↗

Plcg2M28L interacts with high fat-high sugar diet to accelerate Alzheimers disease-relevant phenotypes in mice

Obesity is recognized as a significant risk factor for Alzheimers disease (AD). Studies have supported the notion that obesity accelerates AD-related pathophysiology in mouse models of AD. The majority of studies to date have focused on the use of early-onset AD models. Here we evaluate the impact of genetic risk factors on late-onset AD (LOAD) in mice fed a high fat/high sugar diet. We focused on three mouse models created through the IU/JAX/Pitt MODEL-AD Center, LOAD1, LOAD1.Plcg2M28L and LOAD1.Mthfr677C>T. At 2 months of age, animals were placed on a high fat/high sugar diet (HFD) that induces obesity, or a control diet (CD) that does not, until 12 months of age. Throughout the study, blood was collected to assess cholesterol and glucose. Positron emission tomography/computed tomography (PET/CT) was completed prior to sacrifice to image for glucose utilization and brain perfusion. At the completion of the study, blood and brains were collected for analysis. As expected, animals fed the HFD, regardless of genotype or sex, showed a significant increase in body weight compared to those fed the CD. Glucose and cholesterol increased as a function of HFD as well. Interestingly, LOAD1.Plcg2M28L demonstrated an increase in microglia density as well as alterations in regional brain glucose and perfusion when on a HFD. These changes were not observed in LOAD1 or LOAD1.Mthfr677C>T animals when fed a HFD. Furthermore, LOAD1.Plcg2M28L but not LOAD1.Mthfr677C>T or LOAD1 animals showed transcriptomics correlations to human AD modules. Our results show HFD affects brain health in a genotype-specific manner. Further insight into this process may have significant implications in the development of lifestyle interventions for treatment of AD.

neuroscience↗

De Novo Design of Immunoglobulin-like Domains

Antibodies and antibody derivatives such as nanobodies contain immunoglobulin-like (Ig) {beta}-sandwich scaffolds which anchor the hypervariable antigen-binding loops and constitute the largest growing class of drugs. Current engineering strategies for this class of compounds rely on naturally existing Ig frameworks, which can be hard to modify and have limitations in manufacturability, designability and range of action. Here we develop design rules for the central feature of the Ig fold architecture - the non-local cross-{beta} structure connecting the two {beta}-sheets - and use these to de novo design highly stable seven-stranded Ig domains, confirm their structures through X-ray crystallography, and show they can correctly scaffold functional loops. Our approach opens the door to the design of a new class of antibody-like scaffolds with tailored structures and superior biophysical properties.

biochemistry↗

Characterizing disease-associated human proteins without available protein structures or homologues

Mutations in human proteins lead to diseases. The structure of these proteins can help understand the mechanism of such diseases and develop therapeutics against them. With improved deep learning techniques such as RoseTTAFold and AlphaFold, we can predict the structure of proteins even in the absence of structural homologues. We modeled and extracted the domains from 553 disease-associated human proteins without known protein structures or close homologues in the Protein Databank (PDB). We noticed that the model quality was higher and the RMSD lower between AlphaFold and RoseTTAFold models for domains that could be assigned to CATH families as compared to those which could only be assigned to Pfam families of unknown structure or could not be assigned to either. We predicted ligand-binding sites, protein-protein interfaces, conserved residues in these predicted structures. We then explored whether the disease-associated missense mutations were in the proximity of these predicted functional sites, if they destabilized the protein structure based on ddG calculations or if they were predicted to be pathogenic. We could explain 80% of these disease-associated mutations based on proximity to functional sites, structural destabilization or pathogenicity. When compared to polymorphisms a larger percentage of disease associated missense mutations were buried, closer to predicted functional sites, predicted as destabilising and/or pathogenic. Usage of models from the two state-of-the-art techniques provide better confidence in our predictions, and we explain 93 additional mutations based on RoseTTAFold models which could not be explained based solely on AlphaFold models.

bioinformatics↗

Deep learning methods for designing proteins scaffolding functional sites

Current approaches to de novo design of proteins harboring a desired binding or catalytic motif require pre-specification of an overall fold or secondary structure composition, and hence considerable trial and error can be required to identify protein structures capable of scaffolding an arbitrary functional site. Here we describe two complementary approaches to the general functional site design problem that employ the RosettaFold and AlphaFold neural networks which map input sequences to predicted structures. In the first "constrained hallucination" approach, we carry out gradient descent in sequence space to optimize a loss function which simultaneously rewards recapitulation of the desired functional site and the ideality of the surrounding scaffold, supplemented with problem-specific interaction terms, to design candidate immunogens presenting epitopes recognized by neutralizing antibodies, receptor traps for escape-resistant viral inhibition, metalloproteins and enzymes, and target binding proteins with designed interfaces expanding around known binding motifs. In the second "missing information recovery" approach, we start from the desired functional site and jointly fill in the missing sequence and structure information needed to complete the protein in a single forward pass through an updated RoseTTAFold trained to recover sequence from structure in addition to structure from sequence. We show that the two approaches have considerable synergy, and AlphaFold2 structure prediction calculations suggest that the approaches can accurately generate proteins containing a very wide array of functional sites.

biochemistry↗

Computational design of nanoscale rotational mechanics in de novo protein assemblies

Natural nanomachines like the F1/F0-ATPase contain protein components that undergo rotation relative to each other. Designing such mechanically constrained nanoscale protein architectures with internal degrees of freedom is an outstanding challenge for computational protein design. Here we explore the de novo construction of protein rotary machinery from designed axle and ring components. Using cryoelectron microscopy, we find that axle-ring systems assemble as designed and populate diverse rotational states depending on symmetry match or mismatch and the designed interface energy landscape. These mechanical systems with internal rotational degrees of freedom are a step towards the systematic design of genetically encodable nanomachines. One-Sentence SummaryComputationally designed self-assembling protein rotary machines sample internal degrees of freedom sculpted within the energy landscape.

synthetic biology↗

Time-tagged ticker tapes for intracellular recordings

A core taken in a tree today can reveal climate events from centuries past. Here we adapt this idea to record histories of neural activation. We engineered slowly growing intracellular protein fibers which can incorporate diverse fluorescent marks during growth to store linear ticker tape-like histories. An embedded HaloTag reporter incorporated user-supplied HaloTag-ligand dyes, leading to colored stripes whose boundaries mapped fiber growth to wall-clock time. A co-expressed eGFP tag driven by the cFos immediate early gene promoter recorded the history of neural activity. High-resolution multispectral imaging on fixed samples read the cellular histories. We demonstrated recordings of cFos activation in ensembles of cultured neurons with a single-cell absolute accuracy of approximately 39 min over a 12-hour interval. Protein-based ticker tapes have the potential to achieve massively parallel single-cell recordings of multiple physiological modalities.

neuroscience↗

Natural and designed proteins inspired by extremotolerant organisms can form condensates and attenuate apoptosis in human cells

Many organisms can survive extreme conditions and successfully recover to normal life. This extremotolerant behavior has been attributed in part to repetitive, amphipathic, and intrinsically disordered proteins that are upregulated in the protected state. Here, we assemble a library of approximately 300 naturally-occurring and designed extremotolerance-associated proteins to assess their ability to protect human cells from chemically-induced apoptosis. We show that several proteins from tardigrades, nematodes, and the Chinese giant salamander are apoptosis protective. Notably, we identify a region of the human ApoE protein with similarity to extremotolerance-associated proteins that also protects against apoptosis. This region mirrors the phase separation behavior seen with such proteins, like the tardigrade protein CAHS2. Moreover, we identify a synthetic protein, DHR81, that shares this combination of elevated phase separation propensity and apoptosis protection. Finally, we demonstrate that driving protective proteins into the condensate state increases apoptosis protection, and highlight the ability for DHR81 condensates to sequester caspase-7. Taken together, this work draws a link between extremotolerance-associated proteins, condensate formation, and designing human cellular protection.

synthetic biology↗

Structures of core eukaryotic protein complexes

Protein-protein interactions play critical roles in biology, but despite decades of effort, the structures of many eukaryotic protein complexes are unknown, and there are likely many interactions that have not yet been identified. Here, we take advantage of recent advances in proteome-wide amino acid coevolution analysis and deep-learning-based structure modeling to systematically identify and build accurate models of core eukaryotic protein complexes, as represented within the Saccharomyces cerevisiae proteome. We use a combination of RoseTTAFold and AlphaFold to screen through paired multiple sequence alignments for 8.3 million pairs of S. cerevisiae proteins and build models for strongly predicted protein assemblies with two to five components. Comparison to existing interaction and structural data suggests that these predictions are likely to be quite accurate. We provide structure models spanning almost all key processes in Eukaryotic cells for 104 protein assemblies which have not been previously identified, and 608 which have not been structurally characterized. One-sentence summaryWe take advantage of recent advances in proteome-wide amino acid coevolution analysis and deep-learning-based structure modeling to systematically identify and build accurate models of core eukaryotic protein complexes.

biochemistry↗

The role of complex IV activity in the axonal response of mitochondria to demyelination in experimental disease models of multiple sclerosis

Axon loss is a cardinal neuropathological feature of multiple sclerosis (MS). Axonal injury in MS and experimental disease models is most frequently detected in acutely demyelinating regions. Furthermore, acute axonal injury consistently correlates with the extent of inflammatory demyelination. Following lysolecithin-induced demyelination, we recently reported a compensatory response in neurons, where mitochondria move from the cell body to the acutely demyelinated axon and increase the mitochondrial content. We termed this energetics phenomenon, that is also evident in MS, the axonal response of mitochondria to demyelination (ARMD). In the present study, we assessed axonal mitochondrial content as well as axonal mitochondrial respiratory chain complex IV activity (COX) of axons and related these to axonal injury in nine different experimental disease models. We consistently found ARMD in all experimental disease models. However, the increase in mitochondrial content within demyelinated axons was not always accompanied by a proportionate increase in COX activity, particularly in experimental autoimmune encephalomyelitis (EAE). Axonal COX activity inversely correlated with the extent of axonal injury in experimental disease models. Our findings indicate that ARMD is a consistent and prominent finding and emphasises the need to preserve axonal mitochondrial COX activity in inflammatory demyelination, paving the way for the development of novel neuroprotective therapies.

neuroscience↗

A Cellular Reference Resource for the Mouse Urinary Bladder

The urinary bladder functions as a reservoir to store and extrude liquid bodily waste. Significant debate exists as to this tissues cellular composition and genes associated with their functions. We use a repertoire of cell profiling tools to comprehensively define and spatial resolve cell types. We characterize spatially validated, basal-to-luminal gene expression dynamics within the urothelium, the cellular source of most bladder cancers. We define three distinct populations of fibroblasts that spatially organize from the sub-urothelial layer through to the detrusor muscle, clarifying knowledge around these controversial interstitial cells, and associate increased fibroblasts with aging. We overcome challenges of profiling the detrusor muscle, absence from earlier single cell studies, to report on its transcriptome with many novel and neuronal-like features presumably associated with neuromuscular junctions. Our approach provides a blueprint for tissue atlas construction and the data provides the foundation for future studies of bladder function in health and disease.

genomics↗

Robust de novo design of protein binding proteins from target structural information alone

The design of proteins that bind to a specific site on the surface of a target protein using no information other than the three-dimensional structure of the target remains an outstanding challenge. We describe a general solution to this problem which starts with a broad exploration of the very large space of possible binding modes and interactions, and then intensifies the search in the most promising regions. We demonstrate its very broad applicability by de novo design of binding proteins to 12 diverse protein targets with very different shapes and surface properties. Biophysical characterization shows that the binders, which are all smaller than 65 amino acids, are hyperstable and bind their targets with nanomolar to picomolar affinities. We succeeded in solving crystal structures of four of the binder-target complexes, and all four are very close to the corresponding computational design models. Experimental data on nearly half a million computational designs and hundreds of thousands of point mutants provide detailed feedback on the strengths and limitations of the method and of our current understanding of protein-protein interactions, and should guide improvement of both. Our approach now enables targeted design of binders to sites of interest on a wide variety of proteins for therapeutic and diagnostic applications.

synthetic biology↗

Reconfigurable asymmetric protein assemblies through implicit negative design

Asymmetric multi-protein complexes that undergo subunit exchange play central roles in biology, but present a challenge for protein design. The individual components must contain interfaces enabling reversible addition to and dissociation from the complex, but be stable and well behaved in isolation. Here we employ a set of implicit negative design principles to generate beta sheet mediated heterodimers which enable the generation of a wide variety of structurally well defined asymmetric assemblies. Crystal structures of the heterodimers are very close to the design models, and unlike previously designed orthogonal heterodimer sets, the subunits are stable, folded and monomeric in isolation and rapidly assemble upon mixing. Rigid fusion of individual heterodimer halves to repeat proteins yields central assembly hubs that can bind two or three different proteins across different interfaces. We use these connectors to assemble linearly arranged hetero-oligomers with up to 6 unique components, branched hetero-oligomers, closed C4-symmetric two-component rings, and hetero-oligomers assembled on a cyclic homo-oligomeric central hub, and demonstrate such complexes can readily reconfigure through subunit exchange. Our approach provides a general route to designing asymmetric reconfigurable protein systems.

synthetic biology↗

Relaxin/insulin-like family peptide receptor 4 (Rxfp4) expressing hypothalamic neurons modulate food intake and preference in mice

Relaxin/insulin-like-family peptide receptor-4 (RXFP4), the cognate receptor for insulin-like peptide 5 (INSL5), has been implicated in feeding behaviour as Rxfp4 knockout mice display shorter meal durations and reduced high fat diet (HFD) intake. Here, we generated transgenic Rxfp4-Cre mice to explore Rxfp4 expression and physiology. Using this model, we identified Rxfp4 expression in the central nervous system, including in the ventromedial hypothalamus (VMH). Intra-VMH infusion of INSL5 increased HFD and highly palatable liquid meal intake (HPM) of ad libitum fed wildtype mice. Single-cell RNA-sequencing of VMH Rxfp4-expressing cells (RXFP4VMH) defined a cluster of Rxfp4-labelled neurons expressing Esr1, Tac1 and Oxtr, alongside known appetite-modulating neuropeptide receptors (Mc4r, Cckar and Nmur2). Viral tracing demonstrated RXFP4VMH neural projections to the bed nucleus of the stria terminalis, paraventricular hypothalamus, paraventricular thalamus and central nucleus of the amygdala. Utilising designer receptors exclusively activated by designer drugs (DREADDs), we found that whole body chemogenetic inhibition (Di) of Rxfp4-expressing cells, mimicking native INSL5-RXFP4 signalling, increased intake of HFD and HPM, whilst activation (Dq), either at whole body level or specifically within the VMH, reduced HFD and HPM intake and altered food preference. Ablating VMH Rxfp4-expressing cells recapitulated the lower HFD intake phenotype of Rxfp4 knockout mice, resulting in reduced body weight. These findings identify a discrete Rxfp4-expressing neuronal population as a key regulator of food intake and preference and reveal hypothalamic RXFP4 signalling as a target for feeding behaviour manipulation.

physiology↗

A Multiparametric Activity Profiling Platform for Neuron Disease Phenotyping and Drug Screening

Patient stem cell-derived models enable imaging of complex disease phenotypes and the development of scalable drug discovery platforms. Current preclinical methods for assessing cellular activity do not, however, capture the full intricacies of disease-induced disturbances, and instead typically focus on a single parameter, which impairs both the understanding of disease and the discovery of effective therapeutics. Here, we describe a cloud-based image processing and analysis platform that captures the intricate activity profile revealed by GCaMP fluorescent recordings of intracellular calcium changes and enables discovery of molecules that correct 153 parameters that define the amyotrophic lateral sclerosis motor neuron disease phenotype. In a high-throughput screen we identified compounds that revert the multiparametric disease profile to that found in healthy cells, a novel and robust measure of therapeutic potential quite distinct from unidimensional screening. This platform can guide the development of therapeutics that counteract the multifaceted pathological features of diseased cellular activity.

neuroscience↗

Detection of antibodies neutralizing historical and emerging SARS-CoV-2 strains using a thermodynamically coupled de novo biosensor system

With global vaccination efforts against SARS-CoV-2 underway, there is a need for rapid quantification methods for neutralizing antibodies elicited by vaccination and characterization of their strain dependence. Here, we describe a designed protein biosensor that enables sensitive and rapid detection of neutralizing antibodies against wild type and variant SARS-CoV-2 in serum samples. More generally, our thermodynamic coupling approach can better distinguish sample to sample differences in analyte binding affinity and abundance than traditional competition based assays.

molecular biology↗

Accurate prediction of protein structures and interactions using a 3-track network

DeepMind presented remarkably accurate protein structure predictions at the CASP14 conference. We explored network architectures incorporating related ideas and obtained the best performance with a 3-track network in which information at the 1D sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The 3-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables rapid solution of challenging X-ray crystallography and cryo-EM structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate models of protein-protein complexes from sequence information alone, short circuiting traditional approaches which require modeling of individual subunits followed by docking. We make the method available to the scientific community to speed biological research. One-Sentence SummaryAccurate protein structure modeling enables rapid solution of structure determination problems and provides insights into biological function.

bioinformatics↗

Metagenomic investigation of the equine faecal microbiome reveals extensive taxonomic and functional diversity

BackgroundThe horse plays crucial roles across the globe, including in horseracing, as a working and companion animal and as a food animal. The horse hindgut microbiome makes a key contribution in turning a high fiber diet into body mass and horsepower. However, despite its importance, the horse hindgut microbiome remains largely undefined. Here, we applied culture-independent shotgun metagenomics to thoroughbred equine faecal samples to deliver novel insights into this complex microbial community. ResultsWe performed metagenomic sequencing on five equine faecal samples to construct 123 high- or medium-quality metagenome-assembled genomes from Bacteria and Archaea. In addition, we recovered nearly 200 bacteriophage genomes. We document surprising taxonomic and functional diversity, encompassing dozens of novel or unnamed bacterial genera and species, to which we have assigned new Candidatus names. Many of these genera are conserved across a range of mammalian gut microbiomes. ConclusionsOur metagenomic analyses provide new insights into the bacterial, archaeal and bacteriophage components of the horse gut microbiome. The resulting datasets provide a key resource for future high-resolution taxonomic and functional studies on the equine gut microbiome.

genomics↗