Probabilistic modeling of ambient noise in single-cell omics data

Droplet-based single-cell omics, including single-cell RNA sequencing (scRNAseq), single cell CRISPR perturbations (e.g., CROP-seq) and single-cell protein and transcriptomic profiling (e.g., CITE-seq) hold great promise for comprehensive cell profiling and genetic screening at the single cell resolution, yet these technologies suffer from substantial noise, among which ambient signals present in the cell suspension may be the predominant source. Current efforts to address this issue are highly specific to a certain technology, while a universal model to describe the noise across these technologies may reveal this common source thereby improving the denoising accuracy. To this end, we explicitly examined these unexpected signals and observed a predictable pattern in multiple datasets across different technologies. Based on the finding, we developed single cell Ambient Remover (scAR) which uses probabilistic deep learning to deconvolute the observed signals into native and ambient composition. scAR provides an efficient and universal solution to count denoising for multiple types of single-cell omics data, including single cell CRISPR screens, CITE-seq and scRNAseq. It will facilitate the application of single-cell omics technologies.

Yeast Protein as an Easily Accessible Food Source

In recent years, the awareness and willingness of consumers to consume healthy food has grown significantly. In order to meet these needs, scientists are looking for innovative methods of food production, which is a source of easily digestible protein with a balanced amino acid composition. Yeast protein biomass (single cell protein, SPC) is a bioavailable product which is obtained when primarily using as a culture medium inexpensive various waste substrates including agricultural and industrial wastes. With the growing population, yeast protein seems to be an attractive alternative to traditional protein sources such as plants and meat. Moreover, yeast protein biomass also contains trace minerals and vitamins including B-group. Thus, using yeast in the production of protein provides both valuable nutrients and enhances purification of wastes. In conclusion, nutritional yeast protein biomass may be the best option for human and animal nutrition with a low environmental footprint. The rapidly evolving SCP production technology and discoveries from the world of biotechnology can make a huge difference in the future for the key improvement of hunger problems and the possibility of improving world food security. On the market of growing demand for cheap and environmentally clean SPC protein with practically unlimited scale of production, it may soon become one of the ingredients of our food. The review article presents the possibilities of protein production by yeast groups with the use of various substrates as well as the safety of yeast protein used as food.

Co-production of amino acid-rich xylooligosaccharide and single-cell protein from paper mulberry by autohydrolysis and fermentation technologies

Background Autohydrolysis is an extensively investigated pretreatment method due to its environmental friendliness. During autohydrolysis, most xylan from hemicellulose can be converted into xylooligosaccharides (XOS), and cellulose in the autohydrolyzed residues can be transformed into glucose after enzymatic hydrolysis. Both of these are value-added biochemicals in the biorefining process. In this work, paper mulberry (PM), which contains abundant protein, was utilized as a raw material to coproduce XOS and single-cell protein (SCP) through autohydrolysis and fermentation technologies. Results The results showed that 8.3 g of XOS and 1.8 g of amino acids could be recovered in the autohydrolysate (based on 100 g raw material) after autohydrolysis (170 °C, 1 h). Moreover, 5.7 g of low-DP XOS along with 1.8 g of amino acids could be further obtained from the autohydrolysate after hydrolysis with endo-β-1-4-xylanase. In addition, 20.1 g of fermentable monosaccharides was recovered after hydrolyzing the autohydrolyzed PM with cellulase, which can be used to produce 4.8 g of SCP after fermentation with Candida utilis. Conclusion As a valuable application of PM, a novel process is proposed to coproduce amino acid-rich XOS and SCP through autohydrolysis. The carbohydrate of PM is effectively converted to high value-added products.

Time-resolved assessment of single-cell protein secretion by sequencing

Secreted proteins play critical roles in cellular communication and functional orchestration. Methods enabling concurrent measurement of cellular protein secretion, phenotypes and transcriptomes are still unavailable. Here, we describe time-resolved assessment of protein secretion from single cells by sequencing (TRAPS-seq). Released proteins are trapped onto cell surface via affinity matrices, and the captured analytes together with phenotypic markers can be probed by oligonucleotide-barcoded antibodies and simultaneously sequenced with transcriptomes. We used TRAPS-seq to interrogate secretion dynamics of pleiotropic cytokines (IFN-γ, IL-2 and TNF-α) of early activated human T lymphocytes, unraveling limited correlation between cytokine secretion and its transcript abundance with regard to timing and strength. We found that early central memory T cells with CD45RA expression (TCMRA) are the most effective responders in multiple cytokine secretion, and polyfunctionality involves unique yet dynamic combinations of gene signatures over time. TRAPS-seq presents a useful tool for cellular indexing of secretions, phenotypes, and transcriptomes at single-cell resolution.

Single-cell protein analysis reveals metastable states during the transition to a sensory organ fate

Cell fate decisions can be envisioned as bifurcating dynamical systems, and the decision that Drosophila cells make to undergo sensory organ differentiation has been sucessfully described as such. We have extended these studies by focusing on the Senseless protein, which orchestrates the sensory fate transition. Wing cells contain intermediate Senseless numbers prior to their fate transition, after which they express much greater numbers of Senseless molecules as they differentiate. However, the dynamics are not consistent with it being a simple bistable system. Cells with intermediate Senseless are best modeled as residing in four discrete states, each with a distinct protein number and occupying a specific region of the tissue. Although the four states are stable over time, the number of molecules in each state vary with time. Remarkably, the fold-change in molecule number between adjacent states is invariant and robust to absolute protein number variation. Thus, cells transitioning to sensory fates exhibit metastability with relativistic properties.