Culture-free identification of fast-growing cyanobacteria cells by Raman-activated gravity-driven encapsulation and sequencing

By directly converting solar energy and carbon dioxide into biobased products,cyanobacteria are promising chassis for photosynthetic biosynthesis.To make cyanobacterial photosynthetic biosynthesis technology economically feasible on industrial scales,exploring and engineering cyanobacterial chassis and cell factories with fast growth rates and carbon fixation activities facing environmental stresses are of great significance.To simplify and accelerate the screening for fast-growing cyanobacteria strains,a method called Individual Cyanobacteria Vitality Tests and Screening(iCyanVS)was established.We show that the ^(13)C incorporation ratio of carotenoids can be used to measure differences in cell growth and carbon fixation rates in individual cyanobacterial cells of distinct genotypes that differ in growth rates in bulk cultivations,thus greatly accelerating the process screening for fastest-growing cells.The feasibility of this approach is further demonstrated by phenotypically and then genotypically identifying individual cyanobacterial cells with higher salt tolerance from an artificial mutant library via Raman-activated gravity-driven encapsulation and sequencing.Therefore,this method should find broad applications in growth rate or carbon intake rate based screening of cyanobacteria and other photosynthetic cell factories.

Multiple routes toward engineering efficient cyanobacterial photosynthetic biomanufacturing technologies

Developing efficient CO_(2)utilization technologies can alleviate the urgent pressure on energy and the environment.Moreover,these technologies are crucial for achieving the goal of net zero emissions.Microalgae are photoautotrophic microorganisms that are the main sources of primary productivity in the biosphere.Cyanobacteria,the only prokaryotic microalgae,have also been considered as promising chassis for photosynthetic biosynthesis,directly converting solar energy and CO_(2)into various bio-based products.This technological route is called photosynthetic biomanufacturing,and is advantageous to simultaneous carbon fixation and clean production.This review focuses on development mode,application and suggests trends related to the further development of photosynthetic biomanufacturing.With regard to the link between photosynthetic CO_(2)fixation and the production of desired metabolites,we summarized and compared three widely adopted strategies.“Screening to find”,screening a large number of high-quality cyanobacterial resources and analyzing their intracellular metabolites are of significance for screening novel cyanobacterial species with high-value chemicals and properties of industrial relevance.“Engineering to modify”,the emergence and application of synthetic biological tools and metabolic engineering strategies have enhanced the ability to modify different cyanobacterial species to reshape more carbon to flow toward synthetic tailored chemicals.“Stressing to activate”,through special culture conditions and strategies,combined with omics analysis techniques,silent metabolic pathways and functional modules are activated to induce the accumulation of high-value chemicals.This review provides valid and updated information to facilitate the development of photosynthetic biosynthesis route with carbon fixation and clean production,providing specific feasible solutions for net zero emissions.

Artificial intelligence-assisted automatic and index-based microbial single-cell sorting system for One-Cell-One-Tube

Identification,sorting,and sequencing of individual cells directly from in situ samples have great potential for in-depth analysis of the structure and function of microbiomes.In this work,based on an artificial intelligence(AI)-assisted object detection model for cell phenotype screening and a cross-interface contact method for single-cell exporting,we developed an automatic and index-based system called EasySort AUTO,where individual microbial cells are sorted and then packaged in a microdroplet and automatically exported in a precisely indexed,“One-Cell-One-Tube”manner.The target cell is automatically identified based on an AI-assisted object detection model and then mobilized via an optical tweezer for sorting.Then,a crossinterface contact microfluidic printing method that we developed enables the automated transfer of cells from the chip to the tube,which leads to coupling with subsequent single-cell culture or sequencing.The efficiency of the system for single-cell printing is>93%.The throughput of the system for single-cell printing is~120 cells/h.Moreover,>80%of single cells of both yeast and Escherichia coli are culturable,suggesting the superior preservation of cell viability during sorting.Finally,AI-assisted object detection supports automated sorting of target cells with high accuracy from mixed yeast samples,which was validated by downstream single-cell proliferation assays.The automation,index maintenance,and vitality preservation of EasySort AUTO suggest its excellent application potential for single-cell sorting.

Rapid, automated, and reliable antimicrobial susceptibility test from positive blood culture by CAST‐R

Antimicrobial susceptibility tests(ASTs)are pivotal in combating multidrug resistant pathogens,yet they can be time‐consuming,labor‐intensive,and unstable.Using the AST of tigecycline for sepsis as the main model,here we establish an automated system of Clinical Antimicrobials Susceptibility Test Ramanometry(CAST‐R),based on D2O‐probed Raman microspectroscopy.Featuring a liquid robot for sample pretreatment and a machine learning‐based control scheme for data acquisition and quality control,the 3‐h,automated CAST‐R process accelerates AST by>10‐fold,processes 96 paralleled antibiotic‐exposure reactions,and produces high‐quality Raman spectra.The Expedited Minimal Inhibitory Concentration via Metabolic Activity is proposed as a quantitative and broadly applicable parameter for metabolism‐based AST,which shows 99%essential agreement and 93%categorical agreement with the broth microdilution method(BMD)when tested on 100 Acinetobacter baumannii isolates.Further tests on 26 clinically positive blood samples for eight antimicrobials,including tigecycline,meropenem,ceftazidime,ampicillin/sulbactam,oxacillin,clindamycin,vancomycin,and levofloxacin reveal 93%categorical agreement with BMD‐based results.The automation,speed,reliability,and general applicability of CAST‐R suggest its potential utility for guiding the clinical administration of antimicrobials.