CSF1R inhibition is not specific to innate immune cells but also affects T-helper cell differentiation independently of microglia depletion.

Colony-stimulating factor 1 receptor (CSF1R) inhibition has been proposed as a specific method for microglia depletion. However, recent work revealed that in addition to microglia, CSF1R inhibition also affects other innate immune cells, such as peripheral monocytes and tissue-resident macrophages of the lung, liver, spleen, and peritoneum. Here, we show that this effect is not restricted to innate immune cells only but extends to the adaptive immune compartment. CSF1R inhibition alters the transcriptional profile of bone marrow cells that control T helper cell activation. In vivo or ex vivo inhibition of CSF1R profoundly changes the transcriptional profile of CD4+ cells and suppresses Th1 and Th2 differentiation in directionally stimulated and unstimulated cells and independently of microglia depletion. Given that T cells also contribute in CNS pathology, these effects may have practical implications in the interpretation of relevant experimental data.

Microfluidic Enrichment and Computational Analysis of Rare Sequences from Mixed Genomic Samples for Metagenomic Mining.

Many powerful molecular biology tools have their origins in natural systems, including restriction modification enzymes and the CRISPR effectors, Cas9, Cas12, and Cas13. Heightened interest in these systems has led to mining of genomic and metagenomic data to identify new orthologs of these proteins, new types of CRISPR systems, and uncharacterized natural systems with novel mechanisms. To accelerate metagenomic mining, we developed a high-throughput, low-cost droplet microfluidic-based method for enrichment of rare sequences in a mixed starting population. Using a computational pipeline, we then searched in the enriched data for the presence of CRISPR-Cas systems, identifying a previously unknown CRISPR-Cas system. Our approach enables researchers to efficiently mine metagenomic samples for sequences of interest, greatly accelerating the search for nature's treasures.

CSF1R inhibition by a small-molecule inhibitor is not microglia specific; affecting hematopoiesis and the function of macrophages.

Colony-stimulating factor 1 receptor (CSF1R) inhibition has been proposed as a method for microglia depletion, with the assumption that it does not affect peripheral immune cells. Here, we show that CSF1R inhibition by PLX5622 indeed affects the myeloid and lymphoid compartments, causes long-term changes in bone marrow-derived macrophages by suppressing interleukin 1ß, CD68, and phagocytosis but not CD208, following exposure to endotoxin, and also reduces the population of resident and interstitial macrophages of peritoneum, lung, and liver but not spleen. Thus, small-molecule CSF1R inhibition is not restricted to microglia, causing strong effects on circulating and tissue macrophages that perdure long after cessation of the treatment. Given that peripheral monocytes repopulate the central nervous system after CSF1R inhibition, these changes have practical implications for relevant experimental data.

Single Molecule Protein Detection with Attomolar Sensitivity Using Droplet Digital Enzyme-Linked Immunosorbent Assay.

Many proteins are present at low concentrations in biological samples, and therefore, techniques for ultrasensitive protein detection are necessary. To overcome challenges with sensitivity, the digital enzyme-linked immunosorbent assay (ELISA) was developed, which is 1000× more sensitive than conventional ELISA and allows sub-femtomolar protein detection. However, this sensitivity is still not sufficient to measure many proteins in various biological samples, thereby limiting our ability to detect and discover biomarkers. To overcome this limitation, we developed droplet digital ELISA (ddELISA), a simple approach for detecting low protein levels using digital ELISA and droplet microfluidics. ddELISA achieves maximal sensitivity by improving the sampling efficiency and counting more target molecules. ddELISA can detect proteins in the low attomolar range and is up to 25-fold more sensitive than digital ELISA using Single Molecule Arrays (Simoa), the current gold standard tool for ultrasensitive protein detection. Using ddELISA, we measured the LINE1/ORF1 protein, a potential cancer biomarker that has not been previously measured in serum. Additionally, due to the simplicity of our device design, ddELISA is promising for point-of-care applications. Thus, ddELISA will facilitate the discovery of biomarkers that have never been measured before for various clinical applications.

Evolution on the Biophysical Fitness Landscape of an RNA Virus.

Viral evolutionary pathways are determined by the fitness landscape, which maps viral genotype to fitness. However, a quantitative description of the landscape and the evolutionary forces on it remain elusive. Here, we apply a biophysical fitness model based on capsid folding stability and antibody binding affinity to predict the evolutionary pathway of norovirus escaping a neutralizing antibody. The model is validated by experimental evolution in bulk culture and in a drop-based microfluidics that propagates millions of independent small viral subpopulations. We demonstrate that along the axis of binding affinity, selection for escape variants and drift due to random mutations have the same direction, an atypical case in evolution. However, along folding stability, selection and drift are opposing forces whose balance is tuned by viral population size. Our results demonstrate that predictable epistatic tradeoffs between molecular traits of viral proteins shape viral evolution.

A mix-and-read drop-based in vitro two-hybrid method for screening high-affinity peptide binders.

Drop-based microfluidics have recently become a novel tool by providing a stable linkage between phenotype and genotype for high throughput screening. However, use of drop-based microfluidics for screening high-affinity peptide binders has not been demonstrated due to the lack of a sensitive functional assay that can detect single DNA molecules in drops. To address this sensitivity issue, we introduced in vitro two-hybrid system (IVT2H) into microfluidic drops and developed a streamlined mix-and-read drop-IVT2H method to screen a random DNA library. Drop-IVT2H was based on the correlation between the binding affinity of two interacting protein domains and transcriptional activation of a fluorescent reporter. A DNA library encoding potential peptide binders was encapsulated with IVT2H such that single DNA molecules were distributed in individual drops. We validated drop-IVT2H by screening a three-random-residue library derived from a high-affinity MDM2 inhibitor PMI. The current drop-IVT2H platform is ideally suited for affinity screening of small-to-medium-sized libraries (10(3)-10(6)). It can obtain hits within a single day while consuming minimal amounts of reagents. Drop-IVT2H simplifies and accelerates the drop-based microfluidics workflow for screening random DNA libraries, and represents a novel alternative method for protein engineering and in vitro directed protein evolution.

Label-free single-cell protein quantification using a drop-based mix-and-read system.

Quantitative protein analysis of single cells is rarely achieved due to technical difficulties of detecting minute amounts of proteins present in one cell. We develop a mix-and-read assay for drop-based label-free protein analysis of single cells. This high-throughput method quantifies absolute, rather than relative, amounts of proteins and does not involve antibody labeling or mass spectrometry.