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Background and Aims: Social media can provide real-time insight into trends in substance use, addiction, and recovery. Prior studies have leveraged data from platforms such as Reddit and X (formerly Twitter), but evolving policies around data access have threatened their usability in opioid overdose surveillance systems. Here, we evaluate the potential of a broad set of platforms to detect emerging trends in the opioid crisis. Design: We identified 72 online platforms with a substantial global user base or prior citations in opioid-related research. We evaluated each platform's fit with our definition of social media, size of North American user base, and volume of opioid-related discourse. We created a shortlist of 11 platforms that met our criteria. We documented basic characteristics, volume and nature of opioid discussion, official policies regulating drug-related discussion, and data accessibility of shortlisted platforms. Setting: USA and Canada. Measurements: We quantified the volume of opioid discussion by number of platform-specific Google search hits for opioid terms. We captured informal language by including slang generated using a large language model. We report the number of opioid-related hits and proportion of opioid-related hits to hits for common nouns. Findings: We found that TikTok, YouTube, and Facebook have the most potential for use in opioid-related surveillance. TikTok and Facebook have the highest relative amount of drug-related discussions. Language on TikTok was predominantly informal. Many platforms offer data access tools for research, but changing company policies and user norms create instability. The demographics of users varies substantially across platforms. Conclusions: Social media data sources hold promise for detecting trends in opioid use, but researchers must consider the utility, accessibility, and stability of data on each platform. A strategy mixing several platforms may be required to cover all demographics suffering in the epidemic.

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Pharmacogenetics, the study of how interindividual genetic differences affect drug response, does not explain all observed heritable variance in drug response. Epigenetic mechanisms, such as DNA methylation, and histone acetylation may account for some of the unexplained variances. Epigenetic mechanisms modulate gene expression and can be suitable drug targets and can impact the action of nonepigenetic drugs. Pharmacoepigenetics is the field that studies the relationship between epigenetic variability and drug response. Much of this research focuses on compounds targeting epigenetic mechanisms, called epigenetic drugs, which are used to treat cancers, immune disorders, and other diseases. Several studies also suggest an epigenetic role in classical drug response; however, we know little about this area. The amount of information correlating epigenetic biomarkers to molecular datasets has recently expanded due to technological advances, and novel computational approaches have emerged to better identify and predict epigenetic interactions. We propose that the relationship between epigenetics and classical drug response may be examined using data already available by (1) finding regions of epigenetic variance, (2) pinpointing key epigenetic biomarkers within these regions, and (3) mapping these biomarkers to a drug-response phenotype. This approach expands on existing knowledge to generate putative pharmacoepigenetic relationships, which can be tested experimentally. Epigenetic modifications are involved in disease and drug response. Therefore, understanding how epigenetic drivers impact the response to classical drugs is important for improving drug design and administration to better treat disease.

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Dynein light chain 8 (LC8) interacts with intrinsically disordered proteins (IDPs) and influences a wide range of biological processes. It is becoming apparent that among the numerous IDPs that interact with LC8, many contain multiple LC8-binding sites. Although it is established that LC8 forms parallel IDP duplexes with some partners, such as nucleoporin Nup159 and dynein intermediate chain, the molecular details of these interactions and LC8's interactions with other diverse partners remain largely uncharacterized. LC8 dimers could bind in either a paired "in-register" or a heterogeneous off-register manner to any of the available sites on a multivalent partner. Here, using NMR chemical shift perturbation, analytical ultracentrifugation, and native electrospray ionization MS, we show that LC8 forms a predominantly in-register complex when bound to an IDP domain of the multivalent regulatory protein ASCIZ. Using saturation transfer difference NMR, we demonstrate that at substoichiometric LC8 concentrations, the IDP domain preferentially binds to one of the three LC8 recognition motifs. Further, the differential dynamic behavior for the three sites and the size of the fully bound complex confirmed an in-register complex. Dynamics measurements also revealed that coupling between sites depends on the linker length separating these sites. These results identify linker length and motif specificity as drivers of in-register binding in the multivalent LC8-IDP complex assembly and the degree of compositional and conformational heterogeneity as a promising emerging mechanism for tuning of binding and regulation.

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The type VI secretion system (T6SS) is used by gram-negative bacteria to translocate effectors that can antagonize other bacterial cells. Models predict the variation in collections of effector and cognate immunity genes determine competitiveness and can affect the dynamics of populations and communities of bacteria. However, the outcomes of competition cannot be entirely explained by compatibility of effector-immunity (EI) pairs. Here, we characterized the diversity of T6SS loci of plant-pathogenic Agrobacterium tumefaciens and showed that factors other than EI pairs can impact interbacterial competition. All examined strains encode T6SS active in secretion and antagonism against Escherichia coli. The spectra of EI pairs as well as compositions of gene neighborhoods are diverse. Almost 30 in-planta competitions were tested between different genotypes of A. tumefaciens. Fifteen competitions between members of different species-level groups resulted in T6SS-dependent suppression in in-planta growth of prey genotypes. In contrast, ten competitions between members within species-level groups resulted in no significant effect on the growth of prey genotypes. One strain was an exceptional case and, despite encoding a functional T6SS and toxic effector protein, could not compromise the growth of the four tested prey genotypes. The data suggest T6SS-associated EI pairs can influence the competitiveness of strains of A. tumefaciens, but genetic features have a significant role on the efficacy of interbacterial antagonism.

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The bacterial type VI secretion system (T6SS) is a contractile nanomachine dedicated to delivering molecules out of bacterial cells. T6SS-encoding loci are in the genome sequences of many Gram-negative bacteria, and T6SS has been implicated in a plethora of roles. In the majority of cases, the T6SSs deliver effector proteins in a contact-dependent manner to antagonize other bacteria. Current models suggest that the effectors are deployed to influence social interactions in microbial communities. In this chapter, we describe the structure, function, and regulation of the T6SS and its effectors. We provide focus on the T6SS of Agrobacterium tumefaciens, the causative agent of crown gall disease, and relate the role of the T6SS to the ecology of A. tumefaciens.

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