Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding.

Transcription factors (TFs) are primary regulators of gene expression in cells, where they bind specific genomic target sites to control transcription. Quantitative measurements of TF-DNA binding energies can improve the accuracy of predictions of TF occupancy and downstream gene expression in vivo and shed light on how transcriptional networks are rewired throughout evolution. Here, we present a sequencing-based TF binding assay and analysis pipeline (BET-seq, for Binding Energy Topography by sequencing) capable of providing quantitative estimates of binding energies for more than one million DNA sequences in parallel at high energetic resolution. Using this platform, we measured the binding energies associated with all possible combinations of 10 nucleotides flanking the known consensus DNA target interacting with two model yeast TFs, Pho4 and Cbf1. A large fraction of these flanking mutations change overall binding energies by an amount equal to or greater than consensus site mutations, suggesting that current definitions of TF binding sites may be too restrictive. By systematically comparing estimates of binding energies output by deep neural networks (NNs) and biophysical models trained on these data, we establish that dinucleotide (DN) specificities are sufficient to explain essentially all variance in observed binding behavior, with Cbf1 binding exhibiting significantly more nonadditivity than Pho4. NN-derived binding energies agree with orthogonal biochemical measurements and reveal that dynamically occupied sites in vivo are both energetically and mutationally distant from the highest affinity sites.

Targeted identification of glycosylated proteins in the gastric pathogen Helicobacter pylori (Hp).

Virulence of the gastric pathogen Helicobacter pylori (Hp) is directly linked to the pathogen's ability to glycosylate proteins; for example, Hp flagellin proteins are heavily glycosylated with the unusual nine-carbon sugar pseudaminic acid, and this modification is absolutely essential for Hp to synthesize functional flagella and colonize the host's stomach. Although Hp's glycans are linked to pathogenesis, Hp's glycome remains poorly understood; only the two flagellin glycoproteins have been firmly characterized in Hp. Evidence from our laboratory suggests that Hp synthesizes a large number of as-yet unidentified glycoproteins. Here we set out to discover Hp's glycoproteins by coupling glycan metabolic labeling with mass spectrometry analysis. An assessment of the subcellular distribution of azide-labeled proteins by Western blot analysis indicated that glycoproteins are present throughout Hp and may therefore serve diverse functions. To identify these species, Hp's azide-labeled glycoproteins were tagged via Staudinger ligation, enriched by tandem affinity chromatography, and analyzed by multidimensional protein identification technology. Direct comparison of enriched azide-labeled glycoproteins with a mock-enriched control by both SDS-PAGE and mass spectrometry-based analyses confirmed the selective enrichment of azide-labeled glycoproteins. We identified 125 candidate glycoproteins with diverse biological functions, including those linked with pathogenesis. Mass spectrometry analyses of enriched azide-labeled glycoproteins before and after cleavage of O-linked glycans revealed the presence of Staudinger ligation-glycan adducts in samples only after beta-elimination, confirming the synthesis of O-linked glycoproteins in Hp. Finally, the secreted colonization factors urease alpha and urease beta were biochemically validated as glycosylated proteins via Western blot analysis as well as by mass spectrometry analysis of cleaved glycan products. These data set the stage for the development of glycosylation-based therapeutic strategies, such as new vaccines based on natively glycosylated Hp proteins, to eradicate Hp infection. Broadly, this report validates metabolic labeling as an effective and efficient approach for the identification of bacterial glycoproteins.

A microwell platform for high-throughput longitudinal phenotyping and selective retrieval of organoids.

Organoids are powerful experimental models for studying the ontogeny and progression of various diseases including cancer. Organoids are conventionally cultured in bulk using an extracellular matrix mimic. However, bulk-cultured organoids physically overlap, making it impossible to track the growth of individual organoids over time in high throughput. Moreover, local spatial variations in bulk matrix properties make it difficult to assess whether observed phenotypic heterogeneity between organoids results from intrinsic cell differences or differences in the microenvironment. Here, we developed a microwell-based method that enables high-throughput quantification of image-based parameters for organoids grown from single cells, which can further be retrieved from their microwells for molecular profiling. Coupled with a deep learning image-processing pipeline, we characterized phenotypic traits including growth rates, cellular movement, and apical-basal polarity in two CRISPR-engineered human gastric organoid models, identifying genomic changes associated with increased growth rate and changes in accessibility and expression correlated with apical-basal polarity. A record of this paper's transparent peer review process is included in the supplemental information.

Metasurface optofluidics for dynamic control of light fields.

The ability to manipulate light and liquids on integrated optofluidics chips has spurred a myriad of important developments in biology, medicine, chemistry and display technologies. Here we show how the convergence of optofluidics and metasurface optics can lead to conceptually new platforms for the dynamic control of light fields. We first demonstrate metasurface building blocks that display an extreme sensitivity in their scattering properties to their dielectric environment. These blocks are then used to create metasurface-based flat optics inside microfluidic channels where liquids with different refractive indices can be directed to manipulate their optical behaviour. We demonstrate the intensity and spectral tuning of metasurface colour pixels as well as on-demand optical elements. We finally demonstrate automated control in an integrated meta-optofluidic platform to open up new display functions. Combined with large-scale microfluidic integration, our dynamic-metasurface flat-optics platform could open up the possibility of dynamic display, imaging, holography and sensing applications.

uPIC-M: Efficient and Scalable Preparation of Clonal Single Mutant Libraries for High-Throughput Protein Biochemistry.

New high-throughput biochemistry techniques complement selection-based approaches and provide quantitative kinetic and thermodynamic data for thousands of protein variants in parallel. With these advances, library generation rather than data collection has become rate-limiting. Unlike pooled selection approaches, high-throughput biochemistry requires mutant libraries in which individual sequences are rationally designed, efficiently recovered, sequence-validated, and separated from one another, but current strategies are unable to produce these libraries at the needed scale and specificity at reasonable cost. Here, we present a scalable, rapid, and inexpensive approach for creating User-designed Physically Isolated Clonal-Mutant (uPIC-M) libraries that utilizes recent advances in oligo synthesis, high-throughput sample preparation, and next-generation sequencing. To demonstrate uPIC-M, we created a scanning mutant library of SpAP, a 541 amino acid alkaline phosphatase, and recovered 94% of desired mutants in a single iteration. uPIC-M uses commonly available equipment and freely downloadable custom software and can produce a 5000 mutant library at 1/3 the cost and 1/5 the time of traditional techniques.

micrIO: an open-source autosampler and fraction collector for automated microfluidic input-output.

Microfluidic devices are an enabling technology for many labs, facilitating a wide range of applications spanning high-throughput encapsulation, molecular separations, and long-term cell culture. In many cases, however, their utility is limited by a 'world-to-chip' barrier that makes it difficult to serially interface samples with these devices. As a result, many researchers are forced to rely on low-throughput, manual approaches for managing device input and output (IO) of samples, reagents, and effluent. Here, we present a hardware-software platform for automated microfluidic IO (micrIO). The platform, which is uniquely compatible with positive-pressure microfluidics, comprises an 'AutoSipper' for input and a 'Fraction Collector' for output. To facilitate widespread adoption, both are open-source builds constructed from components that are readily purchased online or fabricated from included design files. The software control library, written in Python, allows the platform to be integrated with existing experimental setups and to coordinate IO with other functions such as valve actuation and assay imaging. We demonstrate these capabilities by coupling both the AutoSipper and Fraction Collector to two microfluidic devices: a simple, valved inlet manifold and a microfluidic droplet generator that produces beads with distinct spectral codes. Analysis of the collected materials in each case establishes the ability of the platform to draw from and output to specific wells of multiwell plates with negligible cross-contamination between samples.

Quantitative mapping of protein-peptide affinity landscapes using spectrally encoded beads.

Transient, regulated binding of globular protein domains to Short Linear Motifs (SLiMs) in disordered regions of other proteins drives cellular signaling. Mapping the energy landscapes of these interactions is essential for deciphering and perturbing signaling networks but is challenging due to their weak affinities. We present a powerful technology (MRBLE-pep) that simultaneously quantifies protein binding to a library of peptides directly synthesized on beads containing unique spectral codes. Using MRBLE-pep, we systematically probe binding of calcineurin (CN), a conserved protein phosphatase essential for the immune response and target of immunosuppressants, to the PxIxIT SLiM. We discover that flanking residues and post-translational modifications critically contribute to PxIxIT-CN affinity and identify CN-binding peptides based on multiple scaffolds with a wide range of affinities. The quantitative biophysical data provided by this approach will improve computational modeling efforts, elucidate a broad range of weak protein-SLiM interactions, and revolutionize our understanding of signaling networks.

An Open-Source, Programmable Pneumatic Setup for Operation and Automated Control of Single- and Multi-Layer Microfluidic Devices.

Microfluidic technologies have been used across diverse disciplines (e.g. high-throughput biological measurement, fluid physics, laboratory fluid manipulation) but widespread adoption has been limited in part due to the lack of openly disseminated resources that enable non-specialist labs to make and operate their own devices. Here, we report the open-source build of a pneumatic setup capable of operating both single and multilayer (Quake-style) microfluidic devices with programmable scripting automation. This setup can operate both simple and complex devices with 48 device valve control inputs and 18 sample inputs, with modular design for easy expansion, at a fraction of the cost of similar commercial solutions. We present a detailed step-by-step guide to building the pneumatic instrumentation, as well as instructions for custom device operation using our software, Geppetto, through an easy-to-use GUI for live on-chip valve actuation and a scripting system for experiment automation. We show robust valve actuation with near real-time software feedback and demonstrate use of the setup for high-throughput biochemical measurements on-chip. This open-source setup will enable specialists and novices alike to run microfluidic devices easily in their own laboratories.

Deciphering the bacterial glycocode: recent advances in bacterial glycoproteomics.

Bacterial glycoproteins represent an attractive target for new antibacterial treatments, as they are frequently linked to pathogenesis and contain distinctive glycans that are absent in humans. Despite their potential therapeutic importance, many bacterial glycoproteins remain uncharacterized. This review focuses on recent advances in deciphering the bacterial glycocode, including metabolic glycan labeling to discover and characterize bacterial glycoproteins, lectin-based microarrays to monitor bacterial glycoprotein dynamics, crosslinking sugars to assess the roles of bacterial glycoproteins, and harnessing bacterial glycosylation systems for the efficient production of industrially important glycoproteins.