Supplementary Figure 1: CRISPRa at the endogenous gene target ldhA does not follow predicted trends.Eight scRNA target sites (L1-L8) upstream of the ldhA promoter were selected. Three of the target sites (L5-L7) were within the 40 bp window where CRISPRa is effective (-100 to -60). While L1, L4, and L5 resulted in weak increases in gene expression, there was no apparent relationship between the position of the sites and ldhA expression levels. Gene expression was measured using RT-qPCR. Fold activation represents expression levels relative to an off-target control (hAAVS1). Bars indicate the average values between three technical replicates and black dots indicate the values of individual replicates. Error bars indicate the standard error of the mean between three technical replicates. S3 Supplementary Figure 2: CRISPRa activity depends on the target sequence on the scRNA. Reporter cassettes that differ only by the sequence of the 20 base scRNA target site give a broad range of gene expression levels, demonstrating that the sequence of the scRNA target site can have a substantial effect on CRISPRa. Three new reporter plasmids were constructed where the J306 target site, located at -81 from the TSS, on the J3-J23117-mRFP1 reporter was replaced by the J104, J106, and J108 sequence. Activation at each promoter was tested when CRISPRa was targeted to their cognate scRNA site. The off-target negative control (OT) represents a strain expressing the original reporter with the J306 site and the CRISPRa components to target an offtarget site (J206). Fluorescence/OD 600 values were measured using a plate reader. Bars indicate the average values between three biological replicates. Black dots indicate the values of individual biological replicates. Error bars indicate the standard deviation between biological replicates. S4 S5 Supplementary Figure 3: The sharp positioning dependence of CRISPRa is observed across multiple promoters. A) The sharp positioning requirements of CRISPRa are not significantly affected by the location or composition of the inserted sequence. Reporters were based on the J1-J23117-mRFP1 (Supplementary Figure 3A) with base shifts introduced in different ways. In the J1 reporter A, bases were inserted upstream of the -35 region. In the J1 reporter B, a different sequence was

In bacterial systems, CRISPR-Cas transcriptional activation (CRISPRa) has the potential to dramatically expand our ability to regulate gene expression, but we currently lack a complete understanding of the rules for designing effective guide RNA target sites. We have identified multiple features of bacterial promoters that impose stringent requirements on bacterial CRISPRa target sites. Most importantly, we found that shifting a gRNA target site by 2-4 bases along the DNA target can cause a nearly complete loss in activity. The loss in activity can be rescued by shifting the target site 10-11 bases, corresponding to one full helical turn. Practically, our results suggest that it will be challenging to find a gRNA target site with an appropriate PAM sequence at precisely the right position at arbitrary genes of interest. To overcome this limitation, we demonstrate that a dCas9 variant with expanded PAM specificity allows activation of promoters that cannot be activated by S. pyogenes dCas9. These results provide a roadmap for future engineering efforts to further expand and generalize the scope of bacterial CRISPRa.

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Study Objectives: There is a long-standing debate about the best way to characterize performance deficits on the psychomotor vigilance test (PVT), a widely used assay of cognitive impairment in human sleep deprivation studies. Here, we address this issue through the theoretical framework of the diffusion model and propose to express PVT performance in terms of signal-to-noise ratio (SNR). Methods: From the equations of the diffusion model for one-choice, reaction-time tasks, we derived an expression for a novel SNR metric for PVT performance. We also showed that LSNR-a commonly used log-transformation of SNR-can be reasonably well approximated by a linear function of the mean response speed, LSNR apx . We computed SNR, LSNR, LSNR apx , and number of lapses for 1284 PVT sessions collected from 99 healthy young adults who participated in laboratory studies with 38 hr of total sleep deprivation. Results: All four PVT metrics captured the effects of time awake and time of day on cognitive performance during sleep deprivation. The LSNR had the best psychometric properties, including high sensitivity, high stability, high degree of normality, absence of floor and ceiling effects, and no bias in the meaning of change scores related to absolute baseline performance. Conclusions: The theoretical motivation of SNR and LSNR permits quantitative interpretation of PVT performance as an assay of the fidelity of information processing in cognition. Furthermore, with a conceptual and statistical meaning grounded in information theory and generalizable across scientific fields, LSNR in particular is a useful tool for systems-integrated fatigue risk management.