Sepsis is one of the major causes of death in the US, necessitating rapid treatment with proper antibiotics. Conventional systems for antibiotic susceptibility testing (AST) take far too long (16-24 h) for the timely treatment of sepsis. This is because they rely on measuring optical density, which relates to bacterial growth, to determine the minimal inhibitory concentrations (MICs) of relevant antibiotics. Thus, there is a desperate need for more improved and rapid AST (RAST) systems. The RAST system can also reduce the growing number of clinical problems that are associated with antibiotic resistance caused by methicillin-resistant Staphylococcus aureus, vancomycin-resistant Staphylococcus aureus, and vancomycin-resistant enterococci. In this study, we demonstrate a microfluidic agarose channel (MAC) system that reduces the AST assay time for determining MICs by single bacterial time lapse imaging. The MAC system immobilizes bacteria by using agarose in a microfluidic culture chamber so that single cell growth can be tracked by microscopy. Time lapse images of single bacterial cells under different antibiotic culture conditions were analyzed by image processing to determine MICs. Three standard bacteria from the Clinical and Laboratory Standard Institute (CLSI) were tested with several kinds of antibiotics. MIC values that were well matched with those of the CLSI were obtained within only 3-4 h. We expect that the MAC system can offer rapid diagnosis of sepsis and thus, more efficient and proper medication in the clinical setting.

Shape-encoded silica microparticles for use in multiplexed bioassays were fabricated by using optofluidic maskless lithography (OFML) and tetraethylorthosilicate (TEOS) polymerization. These encoded silica microparticles exhibit excellent bioconjugation properties and negligible non-specific analyte adsorption. Encoded silica microparticles could be useful in a wide variety of applications, including DNA- and protein-based diagnostics.

Spatial mapping of genomic data to tissue context in a high-throughput and high-resolution manner has been challenging due to technical limitations. Here, we describe PHLI-seq, a novel approach that enables high-throughput isolation and genome-wide sequence analysis of single cells or small numbers of cells to construct genomic maps within cancer tissue in relation to the images or phenotypes of the cells. By applying PHLI-seq, we reveal the heterogeneity of breast cancer tissues at a high resolution and map the genomic landscape of the cells to their corresponding spatial locations and phenotypes in the 3D tumor mass.Electronic supplementary materialThe online version of this article (10.1186/s13059-018-1543-9) contains supplementary material, which is available to authorized users.

Epitranscriptomic features, such as single-base RNA editing, are sources of transcript diversity in cancer, but little is understood in terms of their spatial context in the tumour microenvironment. Here, we introduce spatial-histopathological examination-linked epitranscriptomics converged to transcriptomics with sequencing (Select-seq), which isolates regions of interest from immunofluorescence-stained tissue and obtains transcriptomic and epitranscriptomic data. With Select-seq, we analyse the cancer stem cell-like microniches in relation to the tumour microenvironment of triple-negative breast cancer patients. We identify alternative splice variants, perform complementarity-determining region analysis of infiltrating T cells and B cells, and assess adenosine-to-inosine base editing in tumour tissue sections. Especially, in triple-negative breast cancer microniches, adenosine-to-inosine editome specific to different microniche groups is identified.