A top variant identification pipeline for protein engineering.

Understanding the fitness of protein variants with combinatorial mutations is critical for effective protein engineering. In this issue of Cell Systems, Chu et al. present TopVIP, a top variant identification pipeline that enables accurate picking of the greatest number of best-performing protein variants with high-fitness leveraging zero-shot predictor and low-N iterative sampling.

The Transpeptidase Sortase A Binds Nucleic Acids and Mediates Mammalian Cell Labeling.

Wild-type sortase A is an important virulence factor displaying a diverse array of proteins on the surface of bacteria. This protein display relies on the transpeptidase activity of sortase A, which is widely engineered to allow protein ligation and protein engineering based on the interaction between sortase A and peptides. Here an unknown interaction is found between sortase A from Staphylococcus aureus and nucleic acids, in which exogenously expressed engineered sortase A binds oligonucleotides in vitro and is independent of its canonical transpeptidase activity. When incubated with mammalian cells, engineered sortase A further mediates oligonucleotide labeling to the cell surface, where sortase A attaches itself and is part of the labeled moiety. The labeling reaction can also be mediated by many classes of wild-type sortases as well. Cell surface GAG appears involved in sortase-mediated oligonucleotide cell labeling, as demonstrated by CRISPR screening. This interaction property is utilized to develop a technique called CellID to facilitate sample multiplexing for scRNA-seq and shows the potential of using sortases to label cells with diverse oligonucleotides. Together, the binding between sortase A and nucleic acids opens a new avenue to understanding the virulence of wild-type sortases and exploring the application of sortases in biotechnology.

The RNA m6A demethylase ALKBH5 drives emergency granulopoiesis and neutrophil mobilization by upregulating G-CSFR expression.

Emergency granulopoiesis and neutrophil mobilization that can be triggered by granulocyte colony-stimulating factor (G-CSF) through its receptor G-CSFR are essential for antibacterial innate defense. However, the epigenetic modifiers crucial for intrinsically regulating G-CSFR expression and the antibacterial response of neutrophils remain largely unclear. N6-methyladenosine (m6A) RNA modification and the related demethylase alkB homolog 5 (ALKBH5) are key epigenetic regulators of immunity and inflammation, but their roles in neutrophil production and mobilization are still unknown. We used cecal ligation and puncture (CLP)-induced polymicrobial sepsis to model systemic bacterial infection, and we report that ALKBH5 is required for emergency granulopoiesis and neutrophil mobilization. ALKBH5 depletion significantly impaired the production of immature neutrophils in the bone marrow of septic mice. In addition, Alkbh5-deficient septic mice exhibited higher retention of mature neutrophils in the bone marrow and defective neutrophil release into the circulation, which led to fewer neutrophils at the infection site than in their wild-type littermates. During bacterial infection, ALKBH5 imprinted production- and mobilization-promoting transcriptome signatures in both mouse and human neutrophils. Mechanistically, ALKBH5 erased m6A methylation on the CSF3R mRNA to increase the mRNA stability and protein expression of G-CSFR, consequently upregulating cell surface G-CSFR expression and downstream STAT3 signaling in neutrophils. The RIP-qPCR results confirmed the direct binding of ALKBH5 to the CSF3R mRNA, and the binding strength declined upon bacterial infection, accounting for the decrease in G-CSFR expression on bacteria-infected neutrophils. Considering these results collectively, we define a new role of ALKBH5 in intrinsically driving neutrophil production and mobilization through m6A demethylation-dependent posttranscriptional regulation, indicating that m6A RNA modification in neutrophils is a potential target for treating bacterial infections and neutropenia.

Machine learning-based prediction models to guide the selection of Cas9 variants for efficient gene editing.

The increasing emergence of Cas9 variants has attracted broad interest, as these variants were designed to expand CRISPR applications. New Cas9 variants typically feature higher editing efficiency, improved editing specificity, or alternative PAM sequences. To select Cas9 variants and gRNAs for high-fidelity and efficient genome editing, it is crucial to systematically quantify the editing performances of gRNAs and develop prediction models based on high-quality datasets. Using synthetic gRNA-target paired libraries and next-generation sequencing, we compared the activity and specificity of gRNAs of four SpCas9 variants. The nucleotide composition in the PAM-distal region had more influence on the editing efficiency of HiFi Cas9 and LZ3 Cas9. We further developed machine learning models to predict the gRNA efficiency and specificity for the four Cas9 variants. To aid users from broad research areas, the machine learning models for the predictions of gRNA editing efficiency within human genome sites are available on our website.