UNLABELLED: This study introduced the novel concept of Centeredness, a measure of the emotional atmosphere of the family of origin and a target adult individuals perception of feeling safe, accepted, and supported from childhood primary caregivers and other family members. This study developed a Centeredness scale for adult respondents and tested hypotheses that higher levels of overall Centeredness would predict lower levels of depression and anxiety symptoms; suicidal thoughts and behaviors (STBs); and aggressive behavior; and higher levels of life satisfaction. Predictive effects of Centeredness were compared against attachment-related anxiety and avoidance, and adverse and benevolent childhood experiences (ACEs and BCEs). Participants were recruited via the Prolific-Academic (Pro-A) survey panel into two large independent samples of US young adults aged 19-35 years [Sample 1 (test sample), N = 548, 53.5% female, 2.2% gender non-conforming, 68.3% White, recruited before the pandemic; Sample 2 (replication sample), N = 1,198, 56.2% female, 2.3% gender non-conforming, 66.4% White; recruited during the pandemic]. Participants completed the novel Centeredness scale, which showed strong psychometric properties, and standardized, publicly available assessments of childhood experiences and mental health outcomes. Centeredness was the only variable that significantly predicted each mental health outcome across both samples. BCEs predicted all outcomes except aggressive behavior in the test sample. Centeredness and BCEs were also the only two variables that significantly predicted a dimensional mental health composite in both samples. Neither attachment-related anxiety and avoidance nor ACEs were as broadly predictive. The Centeredness scale assesses emotional aspects of childhood family relationships with individuals of diverse backgrounds and family compositions. Clinical and cultural implications are discussed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42844-023-00089-x.

Sequence-specific control of gene expression on a genome-wide scale is an important approach for understanding gene functions and for engineering genetic regulatory systems. We have recently described an RNA-based method, CRISPR interference (CRISPRi), for targeted silencing of transcription in bacteria and human cells. The CRISPRi system is derived from the Streptococcus pyogenes CRISPR (clustered regularly interspaced palindromic repeats) pathway, requiring only the coexpression of a catalytically inactive Cas9 protein and a customizable single guide RNA (sgRNA). The Cas9-sgRNA complex binds to DNA elements complementary to the sgRNA and causes a steric block that halts transcript elongation by RNA polymerase, resulting in the repression of the target gene. Here we provide a protocol for the design, construction and expression of customized sgRNAs for transcriptional repression of any gene of interest. We also provide details for testing the repression activity of CRISPRi using quantitative fluorescence assays and native elongating transcript sequencing. CRISPRi provides a simplified approach for rapid gene repression within 1-2 weeks. The method can also be adapted for high-throughput interrogation of genome-wide gene functions and genetic interactions, thus providing a complementary approach to RNA interference, which can be used in a wider variety of organisms.

Targeted gene regulation on a genome-wide scale is a powerful strategy for interrogating, perturbing, and engineering cellular systems. Here, we develop a method for controlling gene expression based on Cas9, an RNA-guided DNA endonuclease from a type II CRISPR system. We show that a catalytically dead Cas9 lacking endonuclease activity, when coexpressed with a guide RNA, generates a DNA recognition complex that can specifically interfere with transcriptional elongation, RNA polymerase binding, or transcription factor binding. This system, which we call CRISPR interference (CRISPRi), can efficiently repress expression of targeted genes in Escherichia coli, with no detectable off-target effects. CRISPRi can be used to repress multiple target genes simultaneously, and its effects are reversible. We also show evidence that the system can be adapted for gene repression in mammalian cells. This RNA-guided DNA recognition platform provides a simple approach for selectively perturbing gene expression on a genome-wide scale.

In Eukarya, stalled translation induces 40S dissociation and recruitment of the ribosome quality control complex (RQC) to the 60S subunit, which mediates nascent chain degradation. Here we report cryo-electron microscopy structures revealing that the RQC components Rqc2p (YPL009C/Tae2) and Ltn1p (YMR247C/Rkr1) bind to the 60S subunit at sites exposed after 40S dissociation, placing the Ltn1p RING (Really Interesting New Gene) domain near the exit channel and Rqc2p over the P-site transfer RNA (tRNA). We further demonstrate that Rqc2p recruits alanine- and threonine-charged tRNA to the A site and directs the elongation of nascent chains independently of mRNA or 40S subunits. Our work uncovers an unexpected mechanism of protein synthesis, in which a protein--not an mRNA--determines tRNA recruitment and the tagging of nascent chains with carboxy-terminal Ala and Thr extensions ("CAT tails").

Transcription by RNA polymerase (RNAP) is interrupted by pauses that play diverse regulatory roles. Although individual pauses have been studied in vitro, the determinants of pauses in vivo and their distribution throughout the bacterial genome remain unknown. Using nascent transcript sequencing, we identified a 16-nucleotide consensus pause sequence in Escherichia coli that accounts for known regulatory pause sites as well as ~20,000 new in vivo pause sites. In vitro single-molecule and ensemble analyses demonstrate that these pauses result from RNAP-nucleic acid interactions that inhibit next-nucleotide addition. The consensus sequence also leads to pausing by RNAPs from diverse lineages and is enriched at translation start sites in both E. coli and Bacillus subtilis. Our results thus reveal a conserved mechanism unifying known and newly identified pause events.

The genetic interrogation and reprogramming of cells requires methods for robust and precise targeting of genes for expression or repression. The CRISPR-associated catalytically inactive dCas9 protein offers a general platform for RNA-guided DNA targeting. Here, we show that fusion of dCas9 to effector domains with distinct regulatory functions enables stable and efficient transcriptional repression or activation in human and yeast cells, with the site of delivery determined solely by a coexpressed short guide (sg)RNA. Coupling of dCas9 to a transcriptional repressor domain can robustly silence expression of multiple endogenous genes. RNA-seq analysis indicates that CRISPR interference (CRISPRi)-mediated transcriptional repression is highly specific. Our results establish that the CRISPR system can be used as a modular and flexible DNA-binding platform for the recruitment of proteins to a target DNA sequence, revealing the potential of CRISPRi as a general tool for the precise regulation of gene expression in eukaryotic cells.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.