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The adoptive transfer of autologous T cells engineered to express a chimeric antigen receptor (CAR) has emerged as a promising cancer therapy. Despite impressive clinical efficacy, the general application of current CAR-T-cell therapy is limited by serious treatment-related toxicities. One approach to improve the safety of CAR-T cells involves making their activation and proliferation dependent upon adaptor molecules that mediate formation of the immunological synapse between the target cancer cell and T-cell. Here, we describe the design and synthesis of structurally defined semisynthetic adaptors we refer to as "switch" molecules, in which anti-CD19 and anti- CD22 antibody fragments are site-specifically modified with FITC using genetically encoded noncanonical amino acids. This approach allows the precise control over the geometry and stoichiometry of complex formation between CD19- or CD22-expressing cancer cells and a "universal" anti-FITC-directed CAR-T cell. Optimization of this CAR-switch combination results in potent, dose-dependent in vivo antitumor activity in xenograft models. The advantage of being able to titrate CAR-T-cell in vivo activity was further evidenced by reduced in vivo toxicity and the elimination of persistent B-cell aplasia in immune-competent mice. The ability to control CAR-T cell and cancer cell interactions using intermediate switch molecules may expand the scope of engineered T-cell therapy to solid tumors, as well as indications beyond cancer therapy. [ABSTRACT FROM AUTHOR]

Sister-chromatid cohesion is established during S phase when Eco1 acetylates cohesin. In budding yeast, Eco1 activity falls after S phase due to Cdk1-dependent phosphorylation, which triggers ubiquitination by SCFCdc4. We show here that Eco1 degradation requires the sequential actions of Cdk1 and two additional kinases, Cdc7-Dbf4 and the GSK-3 homolog Mck1. These kinases recognize motifs primed by previous phosphorylation, resulting in an ordered sequence of three phosphorylation events on Eco1. Only the latter two phosphorylation sites are spaced correctly to bind Cdc4, resulting in strict discrimination between phosphates added by Cdk1 and by Cdc7. Inhibition of Cdc7 by the DNA damage response prevents Eco1 destruction, allowing establishment of cohesion after S phase. This elaborate regulatory system, involving three independent kinases and stringent substrate selection by a ubiquitin ligase, enables robust control of cohesion establishment during normal growth and after stress. [ABSTRACT FROM AUTHOR]

Global metabolomics has emerged as a powerful tool to interrogate cellular biochemistry at the systems level by tracking alterations in the levels of small molecules. One approach to define cellular dynamics with respect to this dysregulation of small molecules has been to consider metabolic flux as a function of time. While flux measurements have proven effective for model organisms, acquiring multiple time points at appropriate temporal intervals for many sample types (e.g., clinical specimens) is challenging. As an alternative, meta-analysis provides another strategy for delineating metabolic cause and effect perturbations. That is, the combination of untargeted metabolomic data from multiple pairwise comparisons enables the association of specific changes in small molecules with unique phenotypic alterations. We recently developed metabolomic software called metaXCMS to automate these types of higher order comparisons. Here we discuss the potential of metaXCMS for analyzing proteomic datasets and highlight the biological value of combining meta-results from both metabolomic and proteomic analyses. The combined meta-analysis has the potential to facilitate efforts in functional genomics and the identification of metabolic disruptions related to disease pathogenesis. [ABSTRACT FROM AUTHOR]

Two major challenges in proteomics are the large number of proteins and their broad dynamic range in the cell. We exploited the abundance-dependent Michaelis-Menten kinetics of trypsin digestion to selectively digest and deplete abundant proteins with a method we call DigDeAPr. We validated the depletion mechanism with known yeast protein abundances, and we observed greater than threefold improvement in low-abundance human-protein identification and quantitation metrics. This methodology should be broadly applicable to many organisms, proteases and proteomic pipelines. [ABSTRACT FROM AUTHOR]

The ability to perceive and respond to harmful conditions is crucial for the survival of any organism. The transcription factor DAF-16/FOXO is central to these responses, relaying distress signals into the expression of stress resistance and longevity promoting genes. However, its sufficiency in fulfilling this complex task has remained unclear. Using C. elegans, we show that DAF-16 does not function alone but as part of a transcriptional regulatory module, together with the transcription factor HLH-30/TFEB. Under harmful conditions, both transcription factors translocate into the nucleus, where they often form a complex, co-occupy target promoters, and co-regulate many target genes. Interestingly though, their synergy is stimulus-dependent: They rely on each other, functioning in the same pathway, to promote longevity or resistance to oxidative stress, but they elicit heat stress responses independently, and they even oppose each other during dauer formation. We propose that this module of DAF-16 and HLH-30 acts by combinatorial gene regulation to relay distress signals into the expression of specific target gene sets, ensuring optimal survival under each given threat. The transcription factor DAF-16/FOXO is a downstream effector of insulin/insulin-like growth factor signaling and plays an important role in stress resistance and longevity. Here, the authors show that DAF-16/FOXO can form a complex with HLH-30/TFEB to synergistically regulate transcription of target genes in response to certain stress stimuli. [ABSTRACT FROM AUTHOR]

The article focuses on the use of digestion and depletion of abundant proteins that helps in improving proteomic coverage. It focuses on the detection of low-abundance proteins by decreasing the proteolytic background of sampled peptides from high-abundance proteins. Information on Michaelis-Menten competitive-substrate model is presented.