Optimization of Genomewide CRISPR Screens Using AsCas12a and Multi-Guide Arrays.

Genomewide loss-of-function (LOF) screening using clustered regularly interspaced short palindromic repeats (CRISPR) has facilitated the discovery of novel gene functions across diverse physiological and pathophysiological systems. A challenge with conventional genomewide CRISPR-Cas9 libraries is the unwieldy size (60,000-120,000 constructs), which is resource intensive and prohibitive in some experimental contexts. One solution to streamlining CRISPR screening is by multiplexing two or more guides per gene on a single construct, which enables functional redundancy to compensate for suboptimal gene knockout by individual guides. In this regard, AsCas12a (Cpf1) and its derivatives, for example, enhanced AsCas12a (enAsCas12a), have enabled multiplexed guide arrays to be specifically and efficiently processed for genome editing. Prior studies have established that multiplexed CRISPR-Cas12a libraries perform comparably to the larger equivalent CRISPR-Cas9 libraries, yet the most efficient CRISPR-Cas12a library design remains unresolved. In this study, we demonstrate that CRISPR-Cas12a genomewide LOF screening performed optimally with three guides arrayed per gene construct and could be adapted to robotic cell culture without noticeable differences in screen performance. Thus, the conclusions from this study provide novel insight to streamlining genomewide LOF screening using CRISPR-Cas12a and robotic cell culture.

Detecting personal microbiota signatures at artificial crime scenes.

When mapped to the environments we interact with on a daily basis, the 36 million microbial cells per hour that humans emit leave a trail of evidence that can be leveraged for forensic analysis. We employed 16S rRNA amplicon sequencing to map unique microbial sequence variants between human skin and building surfaces in three experimental conditions: over time during controlled and uncontrolled incidental interactions with a door handle, and during multiple mock burglaries in ten real residences. We demonstrate that humans (n = 30) leave behind microbial signatures that can be used to track interaction with various surfaces within a building, but the likelihood of accurately detecting the specific burglar for a given home was between 20-25%. Also, the human microbiome contains rare microbial taxa that can be combined to create a unique microbial profile, which when compared to 600 other individuals can improve our ability to link an individual 'burglar' to a residence. In total, 5512 discriminating, non-singleton unique exact sequence variants (uESVs) were identified as unique to an individual, with a minimum of 1 and a maximum of 568, suggesting some people maintain a greater degree of unique taxa compared to our population of 600. Approximate 60-77% of the unique exact sequence variants originated from the hands of participants, and these microbial discriminators spanned 36 phyla but were dominated by the Proteobacteria (34%). A fitted regression generated to determine whether an intruder's uESVs found on door handles in an office decayed over time in the presence or absence of office workers, found no significant shift in proportion of uESVs over time irrespective of the presence of office workers. While it was possible to detect the correct burglars' microbiota as having contributed to the invaded space, the predictions were very weak in comparison to accepted forensic standards. This suggests that at this time 16S rRNA amplicon sequencing of the built environment microbiota cannot be used as a reliable trace evidence standard for criminal investigations.

Athletic equipment microbiota are shaped by interactions with human skin.

BACKGROUND: Americans spend the vast majority of their lives in built environments. Even traditionally outdoor pursuits, such as exercising, are often now performed indoors. Bacteria that colonize these indoor ecosystems are primarily derived from the human microbiome. The modes of human interaction with indoor surfaces and the physical conditions associated with each surface type determine the steady-state ecology of the microbial community. RESULTS: Bacterial assemblages associated with different surfaces in three athletic facilities, including floors, mats, benches, free weights, and elliptical handles, were sampled every other hour (8 am to 6 pm) for 2 days. Surface and equipment type had a stronger influence on bacterial community composition than the facility in which they were housed. Surfaces that were primarily in contact with human skin exhibited highly dynamic bacterial community composition and non-random co-occurrence patterns, suggesting that different host microbiomes-shaped by selective forces-were being deposited on these surfaces through time. However, bacterial assemblages found on the floors and mats changed less over time, and species co-occurrence patterns appeared random, suggesting more neutral community assembly. CONCLUSIONS: These longitudinal patterns highlight the dramatic turnover of microbial communities on surfaces in regular contact with human skin. By uncovering these longitudinal patterns, this study promotes a better understanding of microbe-human interactions within the built environment.