Borrelia burgdorferi – the etiological agent of Lyme disease. By systematically mapping B. burgdorferi RNA ends at single nucleotide resolution, we delineated complex gene arrangements and operons and mapped untranslated regions (UTRs) and small RNAs (sRNAs). We experimentally tested modes of B. burgdorferi transcription termination and compared our findings to observations in E. coli, P. aeruginosa, and B. subtilis. We discovered 63% of B. burgdorferi RNA 3′ ends map upstream or internal to open reading frames (ORFs), suggesting novel mechanisms of regulation. Northern analysis confirmed the presence of stable 5′ derived RNAs from mRNAs encoding gene products involved in the unique infectious cycle of B. burgdorferi. We suggest these RNAs resulted from premature termination and regulatory events, including forms of cis-acting regulation. For example, we documented that the polyamine spermidine globally influences the generation of truncated mRNAs. In one case, we showed that high spermidine concentrations increased levels of RNA fragments derived from an mRNA encoding a spermidine import system, with a concomitant decrease in levels of the full-length mRNA. Collectively, our findings revealed new insight into transcription termination and uncovered an abundance of potential RNA regulators.Transcription termination is an essential and dynamic process that can tune gene expression in response to diverse molecular signals. Yet, the genomic positions, molecular mechanisms, and regulatory consequences of termination have only been studied thoroughly in model bacteria. We employed complementary RNA-seq approaches to map RNA ends for the transcriptome of the spirochete  Escherichia coli and Bacillus subtilis, much less is known about these processes in other important organisms, such as bacterial pathogens. For example, the fundamental aspects of gene expression have not been studied extensively in the spirochete Borrelia (Borreliella) burgdorferi, the etiological agent of Lyme disease – the foremost vector-borne illness in the United States  that reRho utilization (Rut) sites, which are proposed to be C-rich, G-poor, and unstructured  or Rho-dependent (reviewed in ). Intriniewed in ). Rho priewed in . Rho is  of mRNAs (cis-acting RNA structures have been shown to change in response to temperature (RNA thermometers), translation of small upstream open reading frames (uORFs) or by binding trans-acting factors, such as metabolites (riboswitches), tRNAs, RNA-binding proteins, or small base-pairing RNAs (sRNAs) . sRNAs iewed in . Therefoiewed in ). B. burectivity , but theB. burgdorferi RNA expression, both in culture and during infection, is not well understood. Previous studies examined B. burgdorferi gene expression in simulated murine and tick environments  and 5′ processed RNA ends were previously detected using 5′RNA-seq  in gdorferi  overlook′RNA-seq . Here weB. burgdorferi B31 (WT) were grown in BSKII to mid-logarithmic phase at 35°C and then temperature-shifted (~23°C to 35°C) to stationary phase  operon, which encodes the outer surface protein (OspA) required for B. burgdorferi tick colonization  confirmed co-transcription of SR0754 and pncA. Collectively, these data revealed complex transcriptional units, long UTRs, and multiple 3′ ends. These examples also illustrate how 3′ ends could be reflective of regulatory events and/or be associated with the generation of regulatory sRNAs.We also noted genes that harbored long 5′ UTRs with premature 3′ ends (before the end of the coding sequence). The nfection , had a 3nfection . A previnfection  sRNA . For exan bbb13 . SR0947 B. burgdorferi grown to logarithmic phase. In many cases, these predictions indicate complex gene arrangements. For example, the annotations for the bb0404 and bb0405 genes suggest both genes could be independently transcribed, with the bb0405 5′ UTR overlapping bb0404 and encoding an sRNA (SR0297). bb0404 also harbors a novel 5′ derived sRNA  detected for logarithmic-grown cells using the annotated stop codon . These diewed in ).B. burgdorferi. Therefore, we analyzed the 3′ ends identified by 3′RNA-seq  of intrinsic termination – RNA hairpin formation and a poly-U-tract causing transcriptional pausing to ultimately trigger termination. Sequences 50 nt upstream and 10 nt downstream each 3′ end were analyzed and given an “intrinsic termination score”  has been performed on a variety of bacterial species, including gram-negative E. coli  and Pseuruginosa  and gramsubtilis . The genE. coli . Average terminator secondary structures for each organism were similar to the average structure for B. burgdorferi. The mean stem for B. subtilis was the longest at ~9 nt and B. burgdorferi had the longest average loop at ~11 nt. B. subtilis terminators also harbored the longest stretch of poly-A and -U. MEME analysis of sequences surrounding the 3′ ends with significant intrinsic terminator scores indicated the expected poly-U enrichment for each bacterium. The P. aeruginosa termination logo also contained a conserved C/G rich stem sequence and the B. subtilis logo, which was found in 90.9% of predicted terminators, had the strongest conserved A-track. Collectively, these data indicated general features of intrinsic termination are present across all bacteria examined. However, there were species-specific differences, with fewer B. burgdorferi 3′ ends preceded by canonical intrinsic terminators.Across E. coli , P. aeruruginosa  and B. ssubtilis , G/C usae method . This prB. burgdorferi  sites (reviewed in ). Rho hagdorferi , but no ll death . Total Rll death . Using tE. coli . For example, SR0742, an annotated ~54 nt sRNA on replicon lp21, had significant transcriptional readthrough with a predominant longer form of the sRNA in the +BCM sample . These oE. coli Rho regions identified by ±BCM-seq  termination score  of Rho-termination events overlapped with predicted intrinsic terminations, which is nearly half (45.2%) of all predicted intrinsic termination associated with mRNAs . This wa-regions . Recentl-regions . We selesomerase , had a Rsomerase . The ospon score . The levE. coli could be the result of varied regulation (cis-acting RNA elements (like RNA thermometers and riboswitches). Thus, we collated upstream and ORF-internal 3′ ends that could correspond to such regulatory events for B. burgdorferi . Northern analysis across growth showed a dominant band corresponding to the expected SR0821 size (~82 nt) whose levels clearly increased in the temperature-shifted sample  binding adhesion and 5′ methylthioadenosine/S-adenosyl homocysteine (MTA/SAH) nucleosidase  was observed  was previously reported to harbor a long (~195 nt) 5′ UTR that resulted in a premature transcript of the same length . For thobserved . In contort RNAs . For botmide gel , which ds region . The glye length . Here, we length . The levpotB is the second gene within a putative polycistronic locus. B. burgdorferi is a spermidine auxotroph (potABCD (bb0642-bb0639) locus encodes an essential spermidine importer  documented three predominant products , and two shorter, likely 5′ processed transcripts, at ~228 nt (potB 5′334–561) and ~77 nt   . We conf SR0541) . There wcis-acting regulators, serve an independent function, and/or exist as the byproducts of regulatory events. These events may be influenced by environmental conditions, for example when the levels of a specific metabolite, such as nucleotides, nitrogen, peptides, carbon sources, or polyamines, are changed. To investigate this hypothesis, we exposed B. burgdorferi to spermidine and globally examined transcriptomic changes for 5′ and ORF-internal 3′ ends.In general, the short transcripts that we detected could correspond to cis-acting gene regulation in both eukaryotes and prokaryotes . Three rrelated , and therrelated . We focuWe analyzed the 870 upstream and internal 3′ ends  and calcpotAB locus and found strong enrichment of potB 5′ RNAs in the +spermidine samples  or as separate RNAs of approximately the same size (potA/B) (We examined the  samples . To exam samples . Norther(potA/B) . We also(potA/B)  samples (potA/B) . This im(potA/B) .potB 5′ RNA levels when B. burgdorferi cells were grown to logarithmic phase and then exposed to 0, 5, or 10 mM spermidine for 48 h. Under these conditions, all samples reached stationary phase at approximately the same time. RNA was isolated and northern analysis performed for the potB 5′ RNAs  encodes a cytidine deaminase  or the same sequence with potB 5′1–561 + 33 nt downstream of the premature 3′ end , which fuses the first 61 amino acids of PotB in-frame with luciferase  in luciferase activity was observed with the translational fusion exposed to 10 mM spermidine. These reporter-fusion data corroborated results from our northern analysis and suggest that potB expression is regulated at both the promoter and after transcription-initiation.To investigate if the downregulation of ciferase . We assaciferase . Luciferciferase  and are ciferase . potB prpotB 5′1–561 effect could still occur if driven by another promoter. Thus, we used the same translational luciferase reporter fusion but replaced the potB promoter with the potA promoter by incorporating 200 bp upstream of the potA TSS . In the 5′RNA-seq data, the number of TSS reads for PpotA and PpotB are similar (potA+potB 5′1–594), along with a vector control and a potA transcriptional reporter fusion control  under the same experimental conditions as before -qPCR using primers within SR0541 to measure the levels of potB 5′ RNAs across the tick-mouse enzootic cycle . It is possible a subset of 3′ ends are due to RNA degradation during library preparation. Nevertheless, we think that our data and list , reminiscent of the previous observation that 63.0% of TSSs mapped internal to annotated eri ORFs . Recentlrculosis . TranscrMoving forward, our list of gene annotations  should bE. coli and B. subtilis, but not comprehensively analyzed in B. burgdorferi. Using our datasets, we classified 3′ ends as possible intrinsic terminators if their upstream sequence had features of canonical intrinsic terminators. When we compared our analysis of B. burgdorferi 3′ ends with similar data for E. coli, P. aeruginosa and B. subtilis, we observed the greatest similarity between the predicted intrinsic terminators in E. coli (30.0% of the 884 detected 3′ ends) and B. burgdorferi . Both organisms had a similar putative intrinsic structures and termination logos. It is somewhat surprising that there is not a stronger enrichment of G/C content surrounding B. burgdorferi 3′ ends, but given the A/T rich genome, perhaps limited G/C content in terminators is sufficient for the formation of stable secondary structures. In contrast, P. aeruginosa, which had the highest genomic G/C content of the organisms tested, had a strong enrichment of G/C content at 3′ ends. It should be noted that our classification of intrinsic termination is based on known intrinsic terminators and there could be novel features of B. burgdorferi terminators that prevent their “intrinsic” classification. It has also recently been proposed that most instances of B. subtilis intrinsic termination require the protein factors NusA and/or NusG to facilitate efficient transcription termination , but thochaetes , yet theenticola . We expeE. coli, spermidine induces ribosome stalling at a uORF in the 5′ UTR of the speFL mRNA . The gleFL mRNA  and affetJI mRNA , encodintJI mRNA .B. burgdorferi potB that increased in response to spermidine alongside downregulation of the full-length mRNA. The exact mechanism for this effect deserves additional study. However, given the overlap with the potA and potB coding sequence and the examples in other organisms, we hypothesize that potB 5′ RNAs could reflect the modulation of translation efficiency coupled with premature termination or mRNA cleavage. Our transcriptome-wide mapping of B. burgdorferi 3′ ends in response to spermidine also documented other examples of increased 5′ fragments at the start of coding sequences.We discovered a prematurely generated fragment of B. burgdorferi, spirochete gene regulation and thus the biology of Lyme disease. We documented an abundance of potential cis- and trans-acting regulatory elements that set the stage for future projects to characterize RNA-mediated gene regulation in B. burgdorferi.Our work has led to new insights into the fundamental process of termination in B. burgdorferi strain B31 A3 lacking cp9  genomic DNA and the primers PA553 + PA554 or PA535 + PA536, respectively. The promoter sequences were ligated into PCR-amplified (PA480 + PA481) pJSB161 vector  200 bp upstream the potB TSS along with potB 5′1–561 + 33 nt downstream the dominant potB ORF-internal 3′ end (PpotB+potB 5′1–594), which fuses the first 61 PotB amino acids in-frame with luciferase, and cloned into the pJSB161 vector cut with BlgII and BanII restriction enzymes. The PpotA+potB 5′1–594 translational luciferase reporter fusion plasmid was constructed by ligating PCR-amplified products for PpotA (primers PA601 + PA602) and potB 5′1–594 (primers PA603 + PA594), which harbored an overlapping sequence into PCR-amplified (PA563 + PA590) pJSB161 vector (The luciferase reporter plasmids were generated in NEB 5α  on lp25 . The trapotA TSS  using B.1 vector  using th1 vector  using thB. burgdorferi were cultivated in liquid Barbour-Stoenner-Kelly (BSK) II medium supplemented with gelatin and 6% rabbit serum  at 35°C, temperature shifted to the bench (~23°C) for 48 hours, and then temperature shifted back to 35°C for 48 hours resulting in a stationary culture (2.0×108 – 3.0×108 cells/ml). Growth curves were performed by diluting spirochetes to 1×105 cells/ml and monitoring cell growth at the indicated time points by darkfield microscopy enumeration.it serum  and platit serum . B. burgB. burgdorferi culture was collected by centrifugation, washed once with 1X PBS , and pellets snap frozen in liquid N2. RNA was isolated using TRIzol (Thermo Fisher Scientific) exactly as described previously (2O and quantified using a NanoDrop (Thermo Fisher Scientific).45 ml of a eviously . RNA wasB. burgdorferi B31 (PA003) were grown in BSKII to mid-logarithmic phase (3.75×107 – 5.5×107 cells/ml) at 35°C, the culture split for RNA isolation or temperature shifted (TS) to bench (~23°C), and then back to 35°C and grown to stationary phase (~3.2×108 cells/ml). RNA was extracted as described above, resulting in logarithmic and TS-stationary samples. RNA was analyzed using an Agilent 4200 TapeStation System to check the quality. RNA was prepared for sequencing as described previously  for 2 min at 72°C, followed by an addition of 1X Stop Solution (Invitrogen). Samples were stored on ice following individual fragmentation of each sample. Fragmented-RNA was pooled together and cleaned using the RNA Clean and Concentrator-5 kit (Zymo) according to the manufacturer’s instructions. Library construction continued following the bacterial-sRNA adapted, RNAtag-seq methodology starting at the rRNA removal step  using BWA-MEM. Multimapping reads were filtered using samtools (B. burgdorferi B31 gene annotations GCF_000008685.2 and the updated sRNA annotation described below. BedGraph files were generated using deepTools (Raw sequence reads were processed using lcdb-wf (lcdb.github.io/lcdb-wf/) according to the following steps as previously performed . Raw seqsamtools . UniqueleepTools  on readshttps://github.com/NICHD-BSPC/termseq-peaks and can be used in general for 3′RNA-seq (Term-seq) peak-calling in other bacteria. Termination peaks were subsequently curated according to the following criteria. The single-bp peak coordinate was set to the strongest signal nucleotide within the boundary of the initial broader peak using multiBigWigSummary from deepTools 3.2.1. The most downstream position, relative to the peak orientation, was chosen when several positions were equally strong. Scores from peaks within a distance of up to 100 bp were assessed to select the peak with the highest score among the cluster for further analysis. These curated peaks were used for all analysis herein , a prominence of , and a relative height of 0.75. Peaks for each replicate were then combined using the IDR framework  into a ss herein .Each peak was assigned to one or more classes, based on the intersect function of Bedtools 2.27.1 , ran viaB. burgdorferi strain as 3′RNA-seq was considered. All these 3′ ends were examined for the first upstream feature (either a TSS or an ORF stop codon). Any 3′ end where the first upstream feature was a stop codon was eliminated, unless there was also a TSS ≤ 200 bp upstream the 3′ end. Any 3′ end where a TSS was only 20 bp or less upstream was also eliminated. This resulted in the 3′ end coordinates in 3′ ends were also categorized according to their position relative to mRNA 5′ UTRs and internal mRNA regions . Any 3′ B. burgdorferi logarithmic-grown datasets , ssrS (6S) (SR0136) (rnpB (SR0613), BsrW (SR0412)  (SR0360), DsrA (SR0440) (pncA (bbe22) was updated to include the experimentally determined start codon  were imported to supplement the gene information reported from NCBI. Reference to gene bb0268 as ‘hfq’ was removed, as this gene was previously misannotated. Collectively, these data resulted in otations , as outl(SR0136) , rnpB (S(SR0412) , and Itt(SR0412) . The fol(SR0440)  and IttB(SR0440) . The ORFrt codon . 5′ UTRsrt codon , within Each identified 3′ end and its surrounding sequence  was analyzed using a previously described quantitative model  to scoreB. burgdorferi 3′ ends identified by 3′RNA-seq with 3′ ends and predicted terminators identified in other studies. Specifically, we determined how many of the positions in our list of genome coordinates are within a given distance threshold of a genome coordinate from another study.As detailed in B. burgdorferi termination to other bacteria, we analyzed raw 3′RNA-seq (Term-seq) data from E. coli uginosa  was anaTotal RNA-seq was performed using the same RNA that was used for the 3′RNA-seq library preparations. Total RNA-seq library construction was carried out based on the RNAtag-seq methodology , which wB. burgdorferi B31 (PA003) spirochetes were grown in BSKII to a cell density of 2.75×107 – 4.0×107 cells/ml, the cultures divided and half treated with 100 μg/ml of bicyclomycin benzoate  for 6 h. Total RNA was isolated from the untreated and BCM-treated cultures as described above. The RNA libraries were prepared and processed according to the total RNA-seq procedure, using the RNAtag-seq methodology as described above.Two cultures of https://github.com/gbaniulyte/rhoterm-peaks). The ratio of the read count in a 800 nt region upstream (BCM_us) and downstream (BCM_ds) of each position was compared to the same ratios at the same position in the untreated sample  ((BCM/Untreated) threshold for termination sites was set to ≥ 2.0. Only the position with the highest R(BCM/Untreated) value within an 800 nt window upstream and downstream was reported in −300) to accurately report. No significance scores were calculated for undefined scores. The presence of a Rho region was also indicated for each gene when one was identified on the same strand internal to or 800 bp downstream an mRNA ORF, tRNA or sRNA, in either or both RNA-seq replicates  spirochetes were diluted into BSK-II or BSK-II +10mM spermidine  adjusted to pH 7.8. Cells were collected in stationary phase (~1×108 – 2×108 cells/ml) after ~80 h of growth in BSK-II alone or ~96 h of growth in BSK-II +10mM spermidine. Total RNA was isolated from the untreated and spermidine-treated cultures as described above. The RNA libraries were prepared and processed according to the total RNA-seq procedure using the RNAtag-seq methodology as described above and sequenced using the Nova-seq system.Three cultures of B. burgdorferi; to estimate the expression of such overlapping genes, the quantification was performed two ways, one that included reads overlapping 2 or more features , and one performed with standard quantification parameters that included only reads overlapping a single feature. Differential expression was performed using raw counts provided to DESeq2 v1.30.0 with the following modifications from lfcShrink default parameters: type=“normal”. A gene was considered differentially expressed if the false discovery rate (FDR) was <0.1 (default for DESeq2) for the statistical test that magnitude of the log2-fold change is greater than 0 .Sequencing reads from untreated and spermidine treated samples were aligned to the GCF_000008685.2_ASM868v2 genome by following the same procedures as 3′RNA-seq data analysis for QC, adaptor removal and sequencing read mapping. Raw counts were quantified using featurecounts from the subread package v.2.0.1. Numerous gene features overlap other features in (untreated/spermidine) threshold for spermidine dependency was set to ≥ 2.0. All upstream and ORF-internal 3′ ends were given a spermidine-dependent score ((untreated/spermidine) value calculated across a 50 nt window upstream and downstream each 3′ end. An ‘undefined’ spermidine-dependent score indicates one that could not be calculated due to an absence of reads in one or more ±spermidine 50 nt upstream or downstream regions. A significance score of ‘n/a’ indicates that the spermidine-dependent significance score was too low (< 1e−300) to accurately report. No significance scores were calculated for undefined scores.Processed sequence reads from “Differential expression in ±spermidine conditions” were used. Spermidine-dependent scores were calculated as Rho region score, with the difference that the minus spermidine ratios were compared to the plus spermidine ratios  spirochetes. The inoculum dose was verified by colony forming unit (CFU) counts in solid BSKII medium. Three weeks post inoculation, infection was confirmed by serology, as previously described (Ixodes scapularis larvae (Oklahoma State University) were allowed to feed to repletion on the B. burgdorferi infected mice, as previously described (5B. burgdorferi B31 A3 (PA003) spirochetes. Ten days post inoculation mice were sacrificed and groups of 2 mouse bladders were pooled, snap frozen in liquid nitrogen, and processed for RNA isolation. Infection was confirmed by the reisolation of spirochetes from ear, heart, and joint tissues.For the isolation of spirochete RNA from ticks, six 6–8 week old female C3H/HeN mice (Envigo) were needle inoculated intraperitoneally (80%) and subcutaneously (20%) with 1×10escribed . Approxiescribed . Two weeEunice Kennedy Shriver National Institute of Child Health and Human Development Institutional Animal Care and Use Committee.The National Institutes of Health is accredited by the International Association for Assessment and Accreditation of Laboratory Animal Care. All animals were cared for in compliance with the Guide for the Care and Use of Laboratory Animals. Protocols for all animal experiments were prepared according to the guidelines of the National Institutes of Health, reviewed and approved by the B. burgdorferi B31 (PA003) were grown to mid-logarithmic phase (2.75×107 – 5.25×107 cells/ml), the cultures split for RNA isolation or allowed to grow an additional 48 h to stationary phase (2.18×108 – 3.08×108 cells/ml) in BSKII. Cells were pelleted at the indicated time points, washed once with 1X PBS, and snap frozen in liquid N2. Frozen culture-pellets, tick, or mouse bladder samples were homogenized in ~1 ml TE buffer  containing 0.5 mg/ml lysozyme in gentleMACS M Tubes using a gentleMACS Dissociator . RNA was isolated using a hot phenol/SDS protocol. Briefly, homogenized samples were mixed and incubated with 1% SDS, 0.1 M NaOAc, pH 5.2 and equal parts saturated phenol (pH 6.6) at 64°C for 6 min. Samples were centrifuged for 10 min at 4°C on maximal speed and the upper phase (~0.6 ml) was transferred into a Heavy Phase Lock Gel tube (5 PRIME) with 800 μl of buffer-saturated phenol:chloroform:isoamyl alcohol (25:24:1). Samples were mixed thoroughly by inversion and centrifuged for 7 min at 4°C on maximal speed. The aqueous layer was transferred to a new Heavy Phase Lock Gel tube and 800 μl of chloroform was added. Samples were mixed and spun again. The aqueous layer was removed and ethanol precipitated. RNA pellets were reconstituted in DEPC H2O. For tick RNA samples, any contaminating DNA was removed by treating 1–5 μg of RNA with the TURBO DNase enzyme kit and purified according to the manufacturer’s instructions (ThermoFisher Scientific). For mouse bladder RNA samples, any contaminating DNA was removed by treating 25 μg of RNA with 10 U of DNase I (Roche) for 20 min and purified as previously described , PA635 and PA636 (potB ORF 3′), PA495 and PA496 (ospC), and PA489 and PA490 (recA). The amounts of each transcript were determined using a genomic DNA standard curve for each gene target with 10 ng, 1 ng, 0.1 ng, and 0.01 ng of DNA. Both standard-curve reactions and PCRs using cDNA for each biological replicate were performed in technical duplicate or triplicate. mRNA transcript copy numbers were normalized to recA copies. See cDNA was synthesized from DNase-treated RNA from cell-culture, fed larvae, fed nymph and mouse bladder samples using the iScript Reverse Transcription supermix kit according to the manufacturer’s instructions (Bio-Rad). Parallel cDNA reactions were carried out in the absence of reverse transcriptase. Real-time quantitative PCR reactions were performed using SsoAdvanced universal SYBR green supermix and the following primer pairs: PA630 and PA634 (B. burgdorferi clones were subcultured to a density of 1×105 cells/ml in 15 ml of BSKII and after 48 hours of growth (1.0×107 – 3.5×107cells/ml), pelleted at 4,000 rpm for 10 min. Cells were resuspended in 15 ml of BSKII containing either no spermidine, 5mM spermidine or 10mM spermidine . Prior to resuspension, media containing spermidine was pH adjusted to 7.8 to match BSKII not containing spermidine. After an additional ~40 hours of growth (1.1×108 – 1.7×108 cells/ml), cells were pelleted at 4000 rpm for 10 minutes, washed with phosphate buffered saline (PBS)  and resuspended in 225 μl of PBS. 100 μl of each sample was used to measure the optical density at 600 nm (OD600) using an EnVision 2105 Multimode Plate Reader (PerkinElmer). 93 μl of each sample were loaded into a black, solid bottom 96-well plate (Corning) and combined with 7 μl of 10 mM D-luciferin (Regis) in PBS. The relative luciferase units (RLUs) were determined by measuring photon emission in each well for 2s using the EnVision 2105 Multimode Plate Reader, 5 min after the addition of luciferin. The background RLU was determined measuring a PBS control, which was subtracted from all experimental measurements. Background-subtracted RLUs were normalized to the OD600 value of the same sample (RLU/OD600). All experiments were conducted in biological triplicate. B. burgdorferi harboring an empty vector (PA156) were used as a control for all experiments. See Luciferase assays were modified from . B. burghttps://github.com/NICHD-BSPC/termseq-peaks.The raw sequencing data reported in this paper have been deposited in GEO under accession number GSE222088. Code for calling 3′ ends in 3′RNA-seq sequencing reads can be found at The processed RNA-seq data from this study are available online via UCSC genome browser at the following links:https://genome.ucsc.edu/cgi-bin/hgTracks?hubUrl=https://hpc.nih.gov/~NICHDcore0/storz/trackhubs/Bb_termseq_rnaseq_tmpshift/hub.hub.txt&hgS_loadUrlName=https://hpc.nih.gov/~NICHD-core0/storz/trackhubs/Bb_termseq_rnaseq_tmpshift/session.txt&hgS_doLoadUrl=submit3 total RNA-seq tracks for logarithmic cells (top + bottom strand)3 3′RNA-seq tracks for logarithmic cells (top + bottom strand)3 total RNA-seq tracks for TS-stationary cells (top + bottom strand)3 3′RNA-seq tracks for TS-stationary cells (top + bottom strand)https://genome.ucsc.edu/cgi-bin/hgTracks?hubUrl=https://hpc.nih.gov/~NICHD-core0/storz/trackhubs/borrelia_browser/hub.hub.txt&hgS_loadUrlName=https://hpc.nih.gov/~NICHD-core0/storz/trackhubs/borrelia_browser/session.txt&hgS_doLoadUrl=submit2 5′RNA-seq −TAP tracks for logarithmic cells (top + bottom strand)2 5′RNA-seq +TAP tracks for logarithmic cells (top + bottom strand)2 total RNA-seq tracks for logarithmic cells (top + bottom strand)3 3′RNA-seq tracks for logarithmic cells (top + bottom strand)https://genome.ucsc.edu/cgi-bin/hgTracks?hubUrl=https://hpc.nih.gov/~NICHD-core0/storz/trackhubs/borrelia_BCM/hub.hub.txt&hgS_loadUrlName=https://hpc.nih.gov/~NICHD-core0/storz/trackhubs/borrelia_BCM/session.txt&hgS_doLoadUrl=submit2 −BCM-seq tracks (top + bottom strand)2 +BCM-seq tracks (top + bottom strand)1 3′RNA-seq track representing overlay/average (top + bottom strand)https://genome.ucsc.edu/cgi-bin/hgTracks?hubUrl=https://hpc.nih.gov/~NICHD-core0/storz/trackhubs/borrelia_SPD/hub.hub.txt&hgS_loadUrlName=https://hpc.nih.gov/~NICHD-core0/storz/trackhubs/borrelia_SPD/session.txt&hgS_doLoadUrl=submit3 −spermidine total RNA-seq tracks (top + bottom strand)3 +spermidine total RNA-seq tracks (top + bottom strand)Supplement 1Supplement 2Supplement 3Supplement 4Supplement 5Supplement 6Supplement 7Supplement 8Supplement 9


Escherichia coli that combine the concept of toehold-mediated strand displacement (TMSD) with the switching principles of naturally occurring transcriptional and translational riboswitches. Specifically, for translational activation and repression, we sequestered anti-anti-RBS or anti-RBS sequences, respectively, inside the loop of a stable hairpin domain, which is equipped with a single-stranded toehold region at its 5′ end and is followed by regulated sequences on its 3′ side. A trigger RNA binding to the toehold region can invade the hairpin, inducing a structural rearrangement that results in translational activation or deactivation. We also demonstrate that TMSD can be applied in the context of transcriptional regulation by switching RNA secondary structure involved in Rho-dependent termination. Our designs expand the repertoire of available synthetic riboregulators by a set of RNA switches with no sequence limitation, which should prove useful for the development of robust genetic sensors and circuits.Regulatory RNA molecules have been widely investigated as components for synthetic gene circuits, complementing the use of protein-based transcription factors. Among the potential advantages of RNA-based gene regulators are their comparatively simple design, sequence-programmability, orthogonality, and their relatively low metabolic burden. In this work, we developed a set of riboswitch-inspired riboregulators in  CRISPR and RNAi are based on protein complexes that require the participation of non-coding RNA molecules  of mRNA molecules, which can change their conformation in response to the presence of small metabolites . Most riInspired by such small-molecule dependent RNA regulators, over the past decade a range of synthetic RNA-based regulatory systems have been developed. Such regulators have already been applied in metabolic pathway engineering , in the Among the recently engineered synthetic riboregulators, ‘toehold switch riboregulators’ (or briefly ‘toehold switches’) employ a toehold-mediated strand displacement process , which hCompared to a different approach towards RNA-dependent riboregulators developed earlier , utilizaIn an alternative approach, Chappell et al. developed RNA transcriptional activators , which exploit anti-sense RNAs to regulate the formation of an intrinsic transcriptional terminator located upstream of a reporter gene through a strand invasion process . Both apIn contrast to most naturally occurring riboswitches, toehold switches and STARS take RNA molecules as their input, and are thus ‘sequence-programmable’. This property has been used for the development of in vitro biosensors for the detection of viral nucleic acids ,44, singCurrent designs for synthetic, RNA-triggered riboregulators still exhibit certain shortcomings such as leaky translation in the OFF state and sequence constraints for the trigger RNAs, respectively. These issues compromise the dynamic range and orthogonality of these components, which poses a challenge for the further development of genetic circuitry composed of larger numbers of RNA regulators, and also their potential use as sensors of endogenous RNA molecules. In the present work, we therefore sought to further expand the repertoire of rationally designed toehold regulators whose RNA inputs can be freely chosen. We applied the TMSD principle to a variety of mechanisms of translational and transcriptional regulation, which were inspired by the architecture of naturally occurring riboswitches, and thus combined functional elements of synthetic and natural gene regulators.The overall design of our riboregulators is characterized by a toehold hairpin structure at the 5′UTR, which includes an anti-sense or anti-anti-sense sequence within the loop that is complementary to a functional sequence domain further downstream, followed by an expression platform. Binding of a trigger RNA at the toehold induces an allosteric rearrangement of the switch domain via TMSD, which either leads to premature termination of transcription or to sequestration of the RBS and hence repression of translation initiation . The swiNext to translational activators and repressors, we realized transcriptional activators based on interference with the formation of an intrinsic terminator. Of note, we were also able to demonstrate RNA regulators that utilize a Rho-dependent mechanism, which also allowed the realization of a transcriptional repressor. Combination of translational and transcriptional control on a single transcript enabled the implementation of a genetic NOR gate with an overall enhanced ON/OFF ratio. At present, however, operation of our switches required the relatively high RNA levels provided by transcription with T7 RNA polymerase, limiting their application to synthetic gene circuitry.in vivo performance  (toehold_hairpin), anti-hairpin (ΔGanti-hairpin), and anti-anti-hairpin (ΔGanti-anti-hairpin). Sequences for the hairpin were designed to follow the order: ΔGtoehold_hairpin < ΔGanti-anti-hairpin < ΔGanti-hairpin and ΔGtoehold_hairpin < ΔGanti-hairpin. All RNA structures were designed and simulated using NUPACK  . We theng NUPACK  and RNAfg NUPACK . All ΔG All DNA oligonucleotides were purchased from Eurofins Genomics Germany. Each toehold switch hairpin was PCR amplified from the template annealed from DNA oligos (Supplementary Data - Primer list). Toehold riboregulators and triggers were both controlled by a T7 RNA polymerase promoter. Sequences for the trigger RNA molecules were coded on the same plasmids as the toehold riboregulators. All plasmids were constructed using the 3A assembly  method aE. coli cells:Recombinant plasmids were transformed into chemically and electrically competent 4, 0.1 mM CaCl2, 20 mM glucose) in conical tubes (50mL), with appropriate antibiotics at 37°C for different time durations. .Turbo NEB (glnV44 thi-1 Δ(lac-proAB) galE15 galK16 R (zgb-210::Tn10)TetS endA1 fhuA2 Δ(mcrB-hsdSM)5, (rK–mK–) F′[traD36 proAB + lacIq lacZΔM15]) were used for cloning using a standard protocol, while BL21 DE3  rne131) were used for gene expression. Experiments were performed for three biological replicates collected over separate days. All cloning strains (Turbo NEB) were grown in LB medium (Carl Roth), while the expression strains  were grown in 5 mL M9 minimal medium  RNA isolation protocol. For each biological replicate, a single colony was picked from an LB agar plate of an overnight transformation and precultured in 500 μl of M9 medium containing the appropriate antibiotics for several hours until the OD600 reached a value of 0.5. Volumes of 10 μl each of the precultured cells were added to Conical Tubes containing 4985 μl (1:500 dilution) of antibiotic containing M9 medium and grown for 4 to 5 h under the same incubation condition until the OD600 reached the value 0.5. Then to each culture 5 μl of 1M IPTG was added  to induce the expression of T7 RNA polymerase, followed by further incubation for 3h. After culture, cells were collected from a 1.5 mL volume by centrifugation at 1,000 g. for 5 min. After discarding the supernatant, the remaining cell pellet was suspended in 1 mL of TRIzol reagent and homogenized by pipetting, followed by incubation at room temperature for 5 min. Cell debris was removed by centrifugation at 12,000 g for 2 min. Samples were then transferred into new 2 mL tubes, 200 μl chloroform (Carl Roth) was added and the samples were mixed for 20 s and incubated at room temperature for 3 min. After incubation, the samples were centrifuged for 10 min at 12,000 g at 4°C, and 400 μl of the aqueous layer containing the RNA was transferred into a fresh 1.5 mL tube. 500 μl isopropanol (Carl Roth) were added to the aqueous phase, the sample was inverted and incubated at room temperature for 10 min and then centrifuged for 10 min at 14,000 rpm at 4°C. After centrifugation, the supernatant was discarded, the remaining pellets were properly washed in 1 mL of pre-cooled 70% ethanol (Carl Roth) and centrifuged for 2 min at 14,000 rpm at 4°C. The remaining supernatant was discarded and the samples were dried at room temperature. 40 μl of RNase-free ddH2O were added to resuspend the pellets for further digestion.Total RNA for quantitative PCR (qPCR) experiments was extracted from 2+ dependent RNA hydrolysis. DNase I was denatured by heating at 75°C for 10 minutes. The RNA samples were further purified using an RNA-clean up kit (NEB). The concentration and quality of the purified total RNA samples were quantified via the 260/280 and 260/230 ratios using a Nanodrop 8000 spectrophotometer (Thermo Fisher).Purified total RNA samples were treated with DNase I (NEB) with reaction buffer for 1h to remove the remaining plasmid and genome DNA. After digestion of the DNA, 0.5 M EDTA solution (Invitrogen™) were added to samples (1:100 dilution) to prevent Mg2O (up to 18.5 μl) were incubated for 5 min at 65°C and cooled on ice for 5 min. 1 μl of RevertUP II reverse transcriptase (biotech rabbit), 0.5 μl of Murine RNAse inhibitor (NEB) were then added, and the solution was incubated at 55°C for 1 h, 80°C for 5 min and then stored at − 20°C. qPCR was performed using 5 μl of Lunar qPCR master mix (NEB), 1 μl of cDNA and 0.5 μl of 0.5 μM mCherry qPCR primers (Supplementary Data - Primer list) and up to 10 μl RNase-free ddH2O (dilute cDNA if necessary). A iQ™ 5 real-time PCR machine (BIO-RAD) was used for data collection using the following PCR program: 95°C for 2 min, followed by 30 cycles of 95°C for 15 s and 60°C for 35 s. All of the measurements were followed by melting curve analysis. Strips of 8 Thermo-Tubes in White & Clear Caps (Thermo Fisher) were used for all measurements. Results were analyzed using iQ™ 5 software (BIO-RAD). To quantify the relative abundance of cDNA concentration, a 5-point standard curve covering a 10,000-fold range of quantified linear DNA concentrations was measured and used to determine the relative mCherry cDNA abundance in each sample . Non-template controls were run in parallel to each measurement to check contamination and nonspecific amplification or primer dimers. Additionally, qPCR was performed on total RNA samples to confirm that no DNA plasmid was detected under the same conditions. Melting curves were recorded to confirm that only a single product was amplified.The concentrations of the purified samples were determined with the Nanodrop 8000 spectrophotometer, and then diluted to 500 ng/μl of total RNA in 10 μl RNase-free ddH2O. 1 μl of diluted total RNA, 0.5 μl of 10 μM reverse transcription primer , 2 μl ofin vitro protein synthesis kit  using the standard protocol. In experiments, 10 nM plasmid DNA  was expressed in triplicate. 25 μl of each cell-free reaction mixture was transferred to a 384-well plate (BRAND®), covered with a plate seal  and placed on a CLARIOstar® plate reader. The temperature was controlled at 37°C, and mCherry fluorescence was measured  every 5 min for 5h.All cell-free gene expression reactions were performed using an E. coli electro competent cell  using a standard protocol. E. coli cells were cultured on LB agar plates containing 100 μg/ml antibiotics at 37°C overnight. Three colonies were picked and cultured in M9 medium (500 μl) for 4h, followed by a subculture in 5 ml M9 medium in a centrifuge tube (50 ml). Cells were then cultured in a shaking incubator at 37°C for 4–5h until the absorbance (OD600) reached a value of 0.5. Subsequently, 1mM IPTG wwas added to the cell culture to induce the expression of T7 RNA polymerase. After overnight culture, 250μl of cell culture was transferred to a 96-well plate (IBIDI 96-well square black) and their fluorescence and OD600 was measured using a microplate reader  with the following settings: Excitation/Emission wavelength: 570–20/630–40 nm; Gain value: 1000; focus height: 2.4 mm.We transformed recombinant plasmids containing toehold riboregulators into 600 and fluorescence values for each replicate were first corrected by subtracting the values of a blank measurement with pure culture medium. The ratio of the absorbance-normalized fluorescence intensities (Fluorescence/OD600) was then calculated for the replicates. We calculated mean relative fluorescence intensities values from the replicates, error bars given in the figures represent the standard deviation (s.d.). The ON/OFF ratio (for activation or repression) for each toehold riboregulator was calculated by dividing the relative fluorescence intensities of the corresponding ON and OFF states. A Welch's t-test was calculated to determine statistical significance (P < 0.05 or 0.01) between different experimental conditions. Flow cytometry measurements were performed using a BD FACSMelodyTM instrument. Cells were diluted (1: 500) into phosphate buffered saline (PBS) and then sampled from the cuvette. Error levels for the fluorescence measurements for cells in the ON and OFF states were calculated from the standard deviation of three biological replicates. Data were analysed using FlowJo 10.1r1 software (FLOWJO) . ODStudies of the secondary structure of naturally occurring translational riboswitches have consistently shown ,49,50 thcis-acting regulatory sequence (either an anti-RBS or anti-anti-RBS), which avoids any sequence constraints for the RNA trigger input.For our synthetic riboregulators, we replaced the riboswitch aptamer domain by a toehold hairpin whose switching via TMSD induces refolding of the expression platform. The toehold hairpin contains an unpaired E. coli thiM riboswitch  and repressors (OFF switches) are shown in Figures boswitch , which sTH = −22.30 kcal/mol) and an anti-RBS hairpin . The sum of the free energies of these motifs has to be lower than the alternatively folded anti-anti-RBS hairpin  , which prompts the formation of the anti-anti-RBS hairpin.Thermodynamically, the TMSD-driven refolding process of our toehold riboregulators is driven by the free energy difference (ΔΔGs) between the conformations attained in the ON and OFF states. In order to ensure switchability of our RNA constructs, we adjusted the folding free energies of the RNA structural motifs present in the absence and presence of a trigger RNA molecule. For example, translational activators in the OFF state (in the absence of a trigger RNA) include a toehold hairpin  . BindingFor consistency, we designed the toehold hairpins of all of our riboregulators with the same loop size (15 nt) to ensure similar behavior during the initial TMSD process. By contrast, the stem lengths and loop sizes of the anti-RBS, anti-terminator and anti-rut sequence domains depend on the downstream target RNA sequences and were adjusted individually to meet the design rules and ensure an overall ΔΔG < 0.in vivo performance of the translational activator, its components were cloned into a recombinant plasmid and studied in experiments with E. coli BL21 DE3 in M9 medium. Both trigger RNA and toehold riboregulators were put under the control of T7 RNA polymerase. In order to activate the riboregulators, IPTG (1mM) was added to an E. coli cell culture, which resulted in expression of T7 RNA polymerase (RNAP) by the E.coli BL21 DE3 bacteria. In fact, we found that transcription by T7 RNAP was crucial for the performance of the switches. Experiments with a weaker E.coli promoter led to worse performance or even loss of function  had a higher leak, but an ON/OFF ratio of ≈ 3.8  to compare their performance with the in vivo results. To this end, linear DNA templates containing toehold riboregulators and triggers were added to the cell-free system, and fluorescence intensities were measured with a microplate reader (Methods & Supplementary Methods - In vitro protein expression in cell-free system). The in vitro results were in line with the in vivo experiments, but tended to show a slightly better performance in terms of ON/OFF ratios. The best performing AARH (anti_RBS stem_2) exhibited an ON/OFF ratio of ≈ 4.9  was designed to be lower than the alternatively folded anti-RBS hairpin . In the translational ON state, i.e. in the absence of trigger, the anti-RBS sequence is thus safely sequestered within the loop of the toehold hairpin  is exposed in the nascent RNA and can thus hybridize to a 5′ subsequence of the t22 terminator . In our second design, anti-t22 stem_2 also includes the complementary sequence of the t22 sequence near its 3′ end, which contains the critical guanine nucleotide of the t22 terminator  was used to characterize the steady-state level of all toehold-mCherry mRNAs in the presence and absence of trigger RNAs in E. coli  and aborts transcription by pulling the RNA away from the RNAP and DNA template.Next to transcriptional riboregulators that target intrinsic terminators, we also attempted to control Rho-dependent termination processes. In  control . Termina control ,56 is a E. coli tryptophanase (tna) operon which encodes tryptophanase and permease for tryptophan metabolism  and thus prevents Rho-dependent termination.Based on this mechanism, we first attempted to use a toehold riboregulator to activate access of Rho to the n Figure . AdditiotnaC sequence in a similar manner as in the translational riboregulators described above  process. These riboregulators combine structural features of natural riboswitches, and the switching principle of recently developed synthetic riboregulators. Instead of using a natural, small molecule-responsive RNA aptamer to control the interaction of a cis-regulatory sequence with an expression platform, we placed a regulatory RNA sequence (e.g. an anti-RBS sequence) into the loop region of a toehold hairpin which could be switched by TMSD, inducing refolding of the riboregulator and thus controlling translational initiation or transcriptional termination. Various factors contribute to the observed performance of the translational and transcriptional switches, which relate to the kinetics and thermodynamics of the switches as well as the details of their experimental assessment.In the present work, the performance of the riboregulators was quantified by comparing the endpoint of the fluorescence of bacterial cultures normalized by the density (or OD) in the respective ‘ON’ and ‘OFF’ states of the switches. This enabled us to assess and rank different riboregulator designs with respect to each other. We wish to note, however, that the actual value of the ON/OFF ratio was found highly dependent on the details of the experimental approach. For instance, when investigating previously described toehold riboregulators ,39 with E. coli promoter BBa_J23119) for transcription of either trigger or riboregulator, or both . This naturally occurring anti-RBS hairpin comprises an RBS (aggagc) of lower efficiency compared to that (aggaga) of the other anti-RBS/RBS hairpin stems  can be prevented by appropriate secondary structure, and potentially is more severe in vivo than in the cell-free context. The latter may be the consequence of the ≈ 10-fold lower ribosome concentration in a cell-free system. In agreement with previous findings  and formed hairpin stems of different stability Figure . Indeed,lculator , Supplemlculator , and confindings ,61, we afindings .For our riboregulators, we adopted the sequence of the toehold and its adjacent hairpin loop from a previous study on toehold riboregulators , which hin vivo case, cell-free experiments show a slightly reduced leak in the OFF state of the repressor, which again might be a consequence of the lower ribosome concentration in the cell-free reaction. Due to the reduced leak, the cell-free translational repressor also exhibits a better ON/OFF ratio than in vivo.For translational repressors, kinetic considerations become more important than for the activators. In the presence of trigger RNA, translational repressors need to be switched into a translationally inactive state quick enough to avoid leaky translation from an accessible RBS. Transcription of the riboregulator at a speed of ≈ 10–100 nt/s defines a time window of ≈ 1 s for trigger binding to the toehold and disruption of the toehold hairpin (or prevention of its formation). For our repressors, we therefore designed a relatively strong anti-RBS hairpin that is expected to sequester the RBS following toehold-mediated switching of the toehold hairpin Figure . While oThe function of transcriptional riboswitches, which are based on termination or anti-termination, critically depends on the kinetics of transcription, ligand binding and refolding of the expression platform . Naturalt22 terminator can be suppressed efficiently, when its ‘critical’ guanine nucleotide is included in the anti-terminator/terminator stem, which is in line with the conclusions of previous work  right after the rut site . However, at this point our designs do not appear to be sensitive enough for such sensing tasks. The range of concentrations expected for endogenous RNAs in  ≈ 20 μM . mRNA coo 100 nM , and theo 100 nM . Similaro 100 nM . WhetherIn the case of translational ON-switches, we found that a strong anti-RBS hairpin reduces leaky translation, but also diminishes the switchability of the structure. All other designs – the translational repressors and the transcriptional regulators – depend on a kinetic competition, e.g. either between trigger and ribosome binding, or between trigger binding and transcriptional termination .E.coli of ≈ In the first case, the target molecules would have to be present at similar concentrations or higher than the concentration of free ribosomes, i.e. those not bound to other mRNAs and engaged in translation, which has been estimated to be on the order of 500 nM . In the ocument} , efficieAll these considerations indicate that our current designs only allow detection of RNA species, which are present at relatively high copy numbers, corresponding to concentrations in the μM range. This is consistent with our finding that the riboswitch-inspired riboregulators performed well only when transcribing the triggers and switches from a T7 promoter (see above).in vivo  and promotes RNA hybridization reactions in vivo . Howeverin vivo . As Hfq In principle, RNA-based regulatory mechanisms are ideal for the implementation of cellular computing circuits, as the sequence-specificity of RNA interactions allows a rational design and ‘wiring’ of the different components of the circuits. In this respect, our riboswitch-inspired riboregulators have the benefit that the RNA trigger sequences (the ‘input’) can be independently chosen from the more or less fixed sequences required for gene regulation (i.e. RBS/anti-RBS or terminator/anti-terminator sequences).Input sequences can be chosen independently and orthogonally to trigger their respective toehold hairpins – e.g. the sequences for triggers A and B in the NOR gate demonstrated in Figure However, we also found that combining several switches in the 5′ untranslated region of a single transcript appears to be less modular than naively expected. We attempted to realize a range of other logic gates with this strategy, but in most cases the switches were non-functional or showed poor performance. For instance, an IMPLY gate can be constructed by fusing a translational activator and a translational repressor . For thiPutting several switches in a row appears to be challenging, and our results indicate that the different components do not act independently and thus cannot be combined simply in a modular fashion. Potentially, optimization of such logic gates (or more complex functions) could be achieved with a screening approach combined with machine-learning methodology, as recently demonstrated for toehold switches .The experimental data sets are either included in this submission, the supplemental information, or are available from the authors upon request. Flow cytometry data have been uploaded to the Zenodo repository under DOI: 10.5281/zenodo.5174952gkac275_Supplemental_FilesClick here for additional data file.


Time series data are often observed in ecological monitoring. Frequently, such data exhibit nonlinear trends over time potentially due to complex relationships between observed and auxiliary variables, and there may also be sudden declines over time due to major disturbances. This poses substantial challenges for modeling such data and also for adaptive monitoring. To address this, we propose methods for finding adaptive designs for monitoring in such settings. This work is motivated by a monitoring program that has been established at Scott Reef; a coral reef off the Western coast of Australia. Data collected for monitoring the health of Scott Reef are considered, and semiparametric and interrupted time series modeling approaches are adopted to describe how these data vary over time. New methods are then proposed that enable adaptive monitoring designs to be found based on such modeling approaches. These methods are then applied to find future monitoring designs at Scott Reef where it was found that future information gain is expected to be similar across a variety of different sites, suggesting that no particular location needs to be prioritized at Scott Reef for the next monitoring phase. In addition, it was found that omitting some sampling sites/reef locations was possible without substantial loss in expected information gain, depending upon the disturbances that were observed. The resulting adaptive designs are used to form recommendations for future monitoring in this region, and for reefs where changes in the current monitoring practices are being sought. As the methods used and developed throughout this study are generic in nature, this research has the potential to improve ecological monitoring more broadly where complex data are being collected over time. When complex time series data are observed, new methods for adaptive monitoring are proposed to make recommendations for future coral reef monitoring in the Western coast of Australian, as well as for reefs where changes in the current monitoring practices are being sought. Unfortunately, environmental stressors such as severe cyclones and bleaching events have had a negative impact on coral reefs  the mean response and given covariates ; a monitoring program of a coral reef system off the Western coast of Australia. We leverage information from the historical data through semiparametric and time series modeling approaches. Methods for finding adaptive designs based on such a modeling approach are then proposed, and designs are found under future monitoring scenarios at Scott Reef. These designs are then evaluated and used to provide recommendations for future surveys at Scott Reef and other reef monitoring programs where changes in the sampling practices are being contemplated.2Scott Reef is located 270 km off the coast of North‐Western Australia  for the whole reef system. Similarly, cyclone exposure has been recorded in terms of the number of hours the reef system was exposed to damaging waves  Are some reef locations  within Scott Reef more important than others in providing information on hard coral cover?(2) Which site at each reef location provides the most information about hard coral cover?These two objectives will be addressed through the use of an adaptive design approach which is described in the next section.5Throughout this paper, we consider a Bayesian design framework as information from historical data can be leveraged to inform design selection. There are also other benefits of such a framework including flexible choice of utility functions  and rigorous handling of uncertainty. The approach to find a design in this framework can be split into three stages, as shown in Figure 5.15.1.1ysrt at the s‐th site, in the r‐th reef location at the t‐th survey time s=1,2,3;r=1,…,7;t=1994.83,…,2016.08. We assume that ysrt follows a Binomial distribution (denoted as “BIN”) such that ysrt∼BINn,πsrt where the first parameter n is number of trials and the second parameter πsrt is the probability of success. Here, n is the number of points in a 250 m combined transect length, that is, n=1250, and πsrt can be expressed as πsrt=1/1+exp−μsrt where μsrt denotes the linear predictor of the model, that is, a linear combination of parameters and covariates. Within this linear predictor, a semiparametric modeling approach can be used to provide flexibility in describing the relationship between covariates and the mean response μsrt. This is achieved through the inclusion of an additive term fxsrt where f⋅ is some smooth function of covariate xsrt which could be (for example) the sampling year.Semiparametric regression approaches can be used to capture nonlinear relationships within a regression model and have been considered previously to describe data from coral communities on the Great Barrier Reef , and K is the total number of knots. Here, knot ηk is the sample quantile of the xsrt’s corresponding to the probability k/K+1  should capture at least some of such variation. In addition, there could be variation between sites/reefs that cannot be explained by the available covariate information. In such cases, random effects can be included into the model as follows to capture such variation, where we note that sites are nested within reefs:γsr represents the random effects that are assumed to follow pγsr|λr,logσs where λr∼pλ|logσr, where p represents some distribution, and, logσs and logσr are the logarithm of the standard deviations of the site and reef random effects, respectively. Wood , yh denotes the previously collected hard coral cover data , and Zh are the previously collected time‐varying covariates (for times 1994.83 to 2016.08) where we have shifted notation such that all historical data will now be indexed by h. This will be convenient when considering future monitoring scenarios later in the paper. To estimate the posterior distribution , ξ is aℳ–closed perspective of Bernardo and Smith ; the smooth component (SC); and all available covariates (ALL COV), that is, Time, Bleaching, Cyclone hours, Interrupted 98 , location‐specific covariates impacts, that is, Cyclone Loc2  and Bleaching Loc, and the interaction between Bleaching and Cyclone. The most appropriate model within this class was then determined via the deviance information criterion (DIC) with a preference for the model with the smallest of these values  that is used to guide future sampling. In particular, this can be used to evaluate a design with respect to addressing a given monitoring objective, and this is described in the next section.5.2This section explains how to evaluate designs in terms of achieving a certain monitoring objective Figure , middle 5.2.1d=d1,d2,…,dnst, where ns is the number of sites appearing in a proposed sampling design out of all sites . The usefulness of such a design d can be quantified via what is called a utility function which evaluates how much information will be provided from data y to address a specific monitoring objective. As it is unknown what data will be observed, the expectation of the utility function is taken with respect to this and other unknowns as follows:z represents specific values of the time‐varying covariates which define particular future monitoring scenarios. Further details about these scenarios will be provided later in this section.Define a design as d indicates more has been learned from data collected. Thus, we seek a design d that maximizes the expectation given in Equation  and a Bayesian version of the D‐optimality criterion. We chose KLD  is the controlling parameter for Monte Carlo integration. This approach to approximate the expected utility is outlined in Algorithm d, many datasets need to be simulated based on the given design (line 2). For this purpose, we simulate parameter and random effect values from the prior distribution (line 3). To simulate hard coral cover for the next survey time point t (line 4), we propose a Taylor series expansion around the mean at the last survey point, that is, 2016.08  and a,b are values which with the Taylor series is centered , we will investigate whether some reef locations within Scott Reef have greater utility than others. Accordingly, seven candidate designs were formulated considering all possible combinations where six of seven reef locations will be sampled. The corresponding designs were labeled as SL1, …, SS3 where, for example, design SL1 denotes that no data will be collected from the reef location SL1 for the next survey time. As there will be a relatively small number of potential candidate designs  under this objective, we will enumerate all seven designs to determine the optimal. Next, under Objective (ii), we determine the optimal design consisting of the most informative site (out of the three) at each reef location. To locate these optimal designs, the coordinate‐exchange algorithm was used based on five randomly selected initial designs  were considered. These were: (a) actual covariate data collected at the next survey time  and (b) bleaching and cyclone impacts including an interaction between them at each reef location , respectively. When evaluating this efficiency, to reduce the impact of the stochastic approximation to the expected utility, the evaluation will be repeated 20 times (independently) for d and dL, and the efficiency will be evaluated each time. The mean of these 20 efficiencies will then be taken as the design efficiency.To evaluate the optimal designs that will be found, we will evaluate the amount of information that is expected to be obtained, and compare this to the amount of information that would be obtained if data were collected at all sites/reefs. For this comparison, a design efficiency can be evaluated as follows:Equation ) for a d66.1βi,i=1,…,9 are the regression coefficients and δ1, δ2, and δ3 are random coefficients. The goodness‐of‐fit of this model was assessed and found to be appropriate, see Appendix To select the most appropriate model for the Scott Reef hard coral cover data, we defined a class of models by considering all components described in Section 6.26.2.1Under Objective (i), we aim to determine the relative importance of seven reef locations at Scott Reef. First, disturbance Scenario (a) was considered. For this evaluation, we formulated seven designs i.e., SL1, …, SS3), as described in Section , …, SS3,According to Table Second, we evaluated Objective (i) under the disturbance Scenario (b). The corresponding design efficiencies and expected utility values are provided in Figure σr). This is typically where the largest change from the prior was observed, and thus could potentially be driving the design selection, that is, designs that provide more information on the variability of coral cover between reef locations are being preferred.To explore these design selections, consider that the posterior means will be similar to the prior means, so this should not particularly contribute to the optimal design selection under KLD utility function, see Equation 6.2.2σr again appeared to be a main contributor to these optimal design selections. This indicates that the optimal site combination under a given disturbance scenario provides more information about the between reef variability.Under Objective (ii), we determined the optimal design that consists of the most informative site at each reef location subject to two disturbance scenarios. The selected sites from each reef location into the optimal designs under the two scenarios are reported in Table The optimal designs under the two scenarios have mean efficiencies of 86.28 (5.49)% and 71.18 (2.62)%, respectively. These reductions in mean efficiency indicate that if disturbances are similar to previous years, then minimal sampling  will capture a substantial proportion of information. However, when a variety of disturbance combinations are observed, then there appears to be more information lost, so there might be value to undertaking additional sampling in such cases.7This study developed adaptive design methods using semiparametric and ITS models through utilizing information captured through such modeling to guide future surveys at Scott Reef. We demonstrated the use of such a modeling approach in finding adaptive design when data showed nonlinear trends with some sudden shifts over time. For this purpose, it was shown that changes around major environmental disturbances in ecological monitoring could be accounted for using an ITS regression modeling approach. This enabled prior information from historical data to be appropriately formed when such data potentially exhibit complex ecological relationships.We assessed the importance of reef locations under Objective (i) subject to two disturbance scenarios. The results showed that there was little difference between the selection of which reef location to omit under either scenario. This indicates that the design choice is relatively inconsequential. Also, dropping one reef location resulted in little information loss, allowing the survey effort to be reduced without losing a substantial amount of information about the parameters in the developed model.σr) meaning that we are learning about how coral cover varies between reefs.Under Objective (ii), we found optimal designs consisting of one site at a given reef location based on two disturbance scenarios. This provided insight into the most appropriate site to sample from a given reef location depending on prevailing disturbance conditions. The differences between the optimal designs between these two scenarios suggest that site selection depends on the disturbances that have been observed, and our methods provide a framework with which to make this assessment. Additionally, it appears that the design choices made under Objectives (i) and (ii) are associated with the estimation of the reef random effect standard deviation parameter  is largely controlled by the number of knots in the model. Ideally, there would be enough knots to effectively capture trends in the data but not so many that random variations are being explained. Automatic procedures are available which provide a choice for the number of knots  can be used to determine whether any locations can be prioritized for data collection. Here, it was found that information gain from sites was similar, so no particular location needed to be prioritized over another.After an extensive monitoring period, explore reduced sampling practices as there is potential to reduce sampling effort  without experiencing significant information loss about coral health.Evaluate disturbance patterns at monitoring locations as these can influence information gain, for example, here, it was shown that more information about coral health was obtained when new disturbance patterns were experienced when compared to historical disturbance patterns.On‐going review of monitoring practices is recommended to assess effectiveness of adaptive designs.Pubudu Thilan Abeysiri Wickrama Liyanaarachchige: Conceptualization (lead); formal analysis (lead); investigation (lead); methodology (lead); project administration (lead); software (lead); validation (lead); visualization (lead); writing – original draft (lead). Rebecca Fisher: Conceptualization (lead); validation ; writing – review and editing . Helen Thompson: Conceptualization ; supervision ; writing – review and editing . Patricia Menendez: Conceptualization ; supervision ; writing – review and editing . James Gilmour: Conceptualization ; data curation ; validation . James M. McGree: Conceptualization (lead); funding acquisition (lead); methodology (lead); project administration (lead); supervision (lead); validation ; writing – review and editing (lead).The authors declare no conflicts of interest.Appendix S1–S10Click here for additional data file.


Momordica cochinchinensis or gac fruit has been reported to have several biological activities, including antioxidation, anti-inflammatory, and anticancer activities. However, the effect on cancer cell metastasis has not been extensively studied. With this aim, the extract from the aril part was selected and investigated for prostate cancer cell migration. The aril extracts were prepared as boiled extract, sonicated extract, ethanol extract, and HAE  extract, while the prostate cancer cell models were PC-3 and LNCaP cells. An MTT assay was performed to compare the antiproliferative effect between prostate cancer cells and normal Vero cells. As a result, the sonicated extract had the highest efficiency in PC-3 cells, with IC50 values of 2 mg/mL and 0.59 mg/mL for 48 and 72 h, respectively, while it had less of an effect in LNCaP cells and was not toxic to normal cells. Cell damage was further confirmed using LDH and cell cycle analysis. As a result, the sonicated extract did not cause cell damage or death and only inhibited cell proliferation. The effect on cancer metastasis was further examined by wound healing, transwell migration assays, and western blotting. The results demonstrated that the sonicated extract inhibited PC-3 cell migration and decreased MMP-9 but increased TIMP-1 expression. All these results support that gac fruit is a valuable source for further development as an anticancer agent for prostate cancer patients. Prostate cancer is a disease that occurs from the uncontrolled growth of abnormal cells in the prostate gland. The risk of prostate cancer increases with age, especially after age 50. It has been reported that prostate cancer is the second most common cancer that leads to mortality in older men. In Thailand 2020), 8,630 new prostate cancer cases 9.2%) and 3,837 prostate cancer-related deaths 3.1%) were found .PC-3 cells were seeded in a 6-well plate at a density of 3 × 10p < 0.05 was considered to indicate a statistically significant difference. All experiments were carried out in triplicate.All data generated are presented as the means ± SEM of three independent experiments unless otherwise specified and were analyzed using GraphPad Prism 5.03 software. Multiple comparison analyses were performed using one-way ANOVA  followed by Dunnett's postmultiple comparisons test. 50 values for PC-3 cells were 2.01 ± 0.02 and 0.59 ± 0.02 mg/mL at 48 and 72 h, respectively  and LNCaP (low-aggressive) cells and compared with normal Vero cells (African green monkey kidney) using an MTT assay. The crude aril extracts were prepared with different solvents and methods, including boiling in water, sonication in water, soaking in 80% EtOH, and soaking in H : A : E 2 : 1 : 1) solvent. The maximum final concentration of DMSO (0.5%) was used as the vehicle control. All cells were treated with 0–5 mg/mL of each aril extract for 24, 48, and 72 h. As shown in Figures  : 1 solvectively , while fectively . Both th2O2 was used as a positive control and clearly showed a high LDH release. These results suggested that the sonicated extract did not damage prostate cancer cells; however, it affected their proliferation.In a further experiment, an LDH assay was used to test whether sonicated extract causes damage to PC-3 cells. As shown in To confirm that sonicated extract did not cause cell damage, a cell cycle analysis was performed. Propidium iodide was used for DNA staining, and the amount of DNA content in each cell cycle was determined using a flow cytometer. As shown in Figures To determine the effect of the sonicated extract on prostate cancer cell metastasis, the process of cancer cell migration was chosen as a target for investigation. A wound healing assay was performed by treating PC-3 cells with the sonicated extracts at 0, 2, 4, and 6 mg/mL for 24 h. As shown in Figures To understand how sonicated extract suppresses prostate cancer cell migration, the expression of protein regulators was detected using western blotting. Matrix metalloproteinase-9 (MMP-9) was selected because it is an important enzyme used in prostate cancer cell migration and invasion. Tissue inhibitor of metalloproteinase-1 (TIMP-1), an inhibitor of MMP, was also selected. PC-3 cells were treated with 0, 2, 4, and 6 mg/mL sonicated extract for 24 h. The results showed that sonicated extract significantly decreased MMP-9 expression compared with the untreated control Figures . The expTo determine the number of phenolic compounds, which are secondary metabolites that are mostly found in plants and responsible for plant biological function, the total phenolic content was evaluated in the sonicated extract. As a result, the sonicated extract from gac aril provided 19.99 ± 1.86 mg GAE/g. These results indicated that sonicated extract consists of phenolic compound sources that might affect cell proliferation and/or metastasis processes.M. cochinchinensis or gac fruit was selected in this work. Gac has been reported to have various biological activities, including antioxidant [Prostate cancer is a common cancer found in men that is highly treatable if diagnosed in the early stage. However, many low- and middle-income countries still have a problem with screening and early detection, which cause a high number of deaths from metastatic prostate cancer. Thus, novel efficient treatments, as well as effective therapeutic agents that can overcome metastasis, are needed. Since natural substances from vegetables and fruits are considered valuable sources for anticancer drug development, ioxidant , anti-inioxidant , 16. Sevioxidant . We show50 values of sonicated extract for PC-3 were 2.01 ± 0.02 mg/mL and 0.59 ± 0.02 mg/mL for 48 and 72 h, respectively. The antiproliferative levels of the sonicated extract are in the same range as shown in Wimalasiri's report that the IC50 values of water extract from gac aril for human melanoma cancer cell lines (MM418C1 and D24) were 0.49 mg/mL and 0.73 mg/mL, respectively [2O2, a positive control. LDH is a cytosolic enzyme that is usually used as an indicator of cell death or cytotoxicity. It is rapidly released into the cell culture medium when cells are damaged [γH2A.X, a marker of double-stranded DNA breaks, reduced more efficiently than in normal cells which indicated the activation of DNA repairing machinery [The investigation was performed in both high-metastasis (PC-3) and low-metastasis (LNCaP) human prostate cancer cells compared with Vero cells. The gac aril was prepared with different methods and solvents to obtain different active components. Of the four extracts, boiled extract, sonicated extract, EtOH extract, and HAE extract, the antiproliferative effect against PC-3 and LNCaP cells indicated that sonicated extract gave the highest efficiency. Τhe ICectively . The eff damaged . Cell cy damaged . Overexp damaged –35. Most damaged . The effachinery .The sonicated extract from gac aril also demonstrated an antimetastatic function in prostate cancer cells. As shown in p-hydroxybenzoic acid, chlorogenic acid, caffeic acid, syringic acid, p-coumaric acid, ferulic acid, sinapic acid [As indicated in the previous works, gac aril contains mainly phenolic and flavonoid compounds , 43. Alspic acid . All thepic acid –50. Therpic acid , 45, orapic acid , pancreapic acid , breast pic acid , lung capic acid , prostatpic acid , and brapic acid .M. cochinchinensis or gac fruit as an antimetastatic and anticancer agent. Gac aril extracted with sonication in water suppressed the proliferation of aggressive prostate cancer cells (PC-3). This effect did not interfere with normal Vero cells. Interestingly, the sonicated extract inhibited the migration of prostate cancer cells via the downregulation of MMP-9 and upregulation of TIMP-1. Hence, a sonicated extract from gac aril is worth studying further to add basic knowledge for anticancer drug development from plants.The present study demonstrated the value of