Despite improvements in the CRISPR molecular toolbox, identifying and purifying properly edited clones remains slow, laborious, and low-yield. Here, we establish a method to enable clonal isolation, selection, and expansion of properly edited cells, using OptoElectroPositioning technology for single-cell manipulation on a nanofluidic device. Briefly, after electroporation of primary T cells with CXCR4-targeting Cas9 ribonucleoproteins, single T cells are isolated on a chip and expanded into colonies. Phenotypic consequences of editing are rapidly assessed on-chip with cell-surface staining for CXCR4. Furthermore, individual colonies are identified based on their specific genotype. Each colony is split and sequentially exported for on-target sequencing and further off-chip clonal expansion of the validated clones. Using this method, single-clone editing efficiencies, including the rate of mono- and bi-allelic indels or precise nucleotide replacements, can be assessed within 10 days from Cas9 ribonucleoprotein introduction in cells.

Treatment response assessment for patients with advanced solid tumors is complex and existing methods require greater precision. Current guidelines rely on imaging, which has known limitations, including the time required to show a deterministic change in target lesions. Serial changes in whole-genome (WG) circulating tumor DNA (ctDNA) were used to assess response or resistance to treatment early in the treatment course. Ninety-six patients with advanced cancer were prospectively enrolled (91 analyzed and 5 excluded), and blood was collected before and after initiation of a new, systemic treatment. Plasma cell-free DNA libraries were prepared for either WG or WG bisulfite sequencing. Longitudinal changes in the fraction of ctDNA were quantified to retrospectively identify molecular progression (MP) or major molecular response (MMR). Study endpoints were concordance with first follow-up imaging (FFUI) and stratification of progression-free survival (PFS) and overall survival (OS). Patients with MP (n ¼ 13) had significantly shorter PFS (median 62 days vs. 310 days) and OS (255 days vs. not reached). Sensitivity for MP to identify clinical progression was 54% and specificity was 100%. MP calls were from samples taken a median of 28 days into treatment and 39 days before FFUI. Patients with MMR (n ¼ 27) had significantly longer PFS and OS compared with those with neither call (n ¼ 51). These results demonstrated that ctDNA changes early after treatment initiation inform response to treatment and correlate with long-term clinical outcomes. Once validated, molecular response assessment can enable early treatment change minimizing side effects and costs associated with additional cycles of ineffective treatment.

Microarrays are at the center of a revolution in biotechnology, allowing researchers to screen tens of thousands of genes simultaneously. Typically, they have been used in exploratory research to help formulate hypotheses. In most cases, this phase is followed by a more focused, hypothesis-driven stage in which certain specific biological processes and pathways are thought to be involved. Since a single biological process can still involve hundreds of genes, microarrays are still the preferred approach as proven by the availability of focused arrays from several manufacturers. Because focused arrays from different manufacturers use different sets of genes, each array will represent any given regulatory pathway to a different extent. We argue that a functional analysis of the arrays available should be the most important criterion used in the array selection. We developed Onto-Compare as a database that can provide this functionality, based on the Gene Ontology Consortium nomenclature. We used this tool to compare several arrays focused on apoptosis, oncogenes, and tumor suppressors. We considered arrays from BD Biosciences Clontech, PerkinElmer, Sigma-Genosys, and SuperArray. We showed that among the oncogene arrays, the PerkinElmer MICROMAX oncogene microarray has a better representation of oncogenesis, protein phosphorylation, and negative control of cell proliferation. The comparison of the apoptosis arrays showed that most apoptosis-related biological processes are equally well represented on the arrays considered. However, functional categories such as immune response, cell-cell signaling, cell-surface receptor linked signal transduction, and interleukins are better represented on the Sigma-Genosys Panorama human apoptosis array. At the same time, processes such as cell cycle control, oncogenesis, and negative control of cell proliferation are better represented on the BD Biosciences Clontech Atlas Select human apoptosis array.

BackgroundThe topology of a biological pathway provides clues as to how a pathway operates, but rationally using this topology information with observed gene expression data remains a challenge.ResultsWe introduce a new general-purpose analytic method called Mechanistic Bayesian Networks (MBNs) that allows for the integration of gene expression data and known constraints within a signal or regulatory pathway to predict new downstream pathway targets. The MBN framework is implemented in an open-source Bayesian network learning package, the Python Environment for Bayesian Learning (PEBL). We demonstrate how MBNs can be used by modeling the early steps of the sonic hedgehog pathway using gene expression data from different developmental stages and genetic backgrounds in mouse. Using the MBN approach we are able to automatically identify many of the known downstream targets of the hedgehog pathway such as Gas1 and Gli1, along with a short list of likely targets such as Mig12.ConclusionsThe MBN approach shown here can easily be extended to other pathways and data types to yield a more mechanistic framework for learning genetic regulatory models.

CRISPR-Cas9 gene editing has revolutionized cell engineering and promises to open new doors in gene and cell therapies. Despite improvements in the CRISPR-editing molecular toolbox in cell lines and primary cells, identifying and purifying properly edited clones remains slow, laborious and low-yield. Here, we establish a new method that uses cell manipulation on a chip with Opto-Electronic Positioning (OEP) technology to enable clonal isolation and selection of edited cells. We focused on editing CXCR4 in primary human T cells, a gene that encodes a co-receptor for HIV entry. T cells hold significant potential for cell-based therapy, but the gene-editing efficiency and expansion potential of these cells is limited. We describe here a method to obviate these limitations. Briefly, after electroporation of cells with CXCR4-targeting Cas9 ribonucleoproteins (RNPs), single T cells were isolated on a chip, where they proliferated over time into well-resolved colonies. Phenotypic consequences of genome editing could be rapidly assessed on-chip with cell-surface staining for CXCR4. Furthermore, independent of phenotype, individual colonies could be identified based on their specific genotype at the 5-10 cell stage. Each colony was split and sequentially exported for immediate "ontarget" sequencing and validation, and further off-chip clonal expansion of the validated clones. We were able to assess single-clone editing efficiencies, including the rate of monoallelic and biallelic indels or precise nucleotide replacements. This new method will enable identification and selection of perfectly edited clones within 10 days from Cas9-RNP introduction in cells based on the phenotype and/or genotype.