Self-rated health (SRH) is a single-item measure that is one of the most widely used measures of general health in population health research. Relatively little is known about changes and the trajectories of SRH in people with chronic medical conditions. The aims of the present study were to identify and describe longitudinal trajectories of self-rated health (SRH) status in people with diabetes.A prospective community study was carried out between 2008 and 2011. SRH was assessed at baseline and yearly at follow-ups (n=1288). Analysis was carried out through trajectory modeling. The trajectory groups were subsequently compared at 4 years follow-up with respect to functioning.Four distinct trajectories of SRH were identified: 1) 72.2% of the participants were assigned to a persistently good SRH trajectory; 2) 10.1% were assigned to a persistently poor SRH trajectory; 3) mean SRH scores changed from good to poor for one group (7.3%); while 4) mean SRH scores changed from poor to medium/good for another group (10.4%). Those with a persistently poor perception of health status were at higher risk for poor functioning at 4 years follow-up than those whose SRH scores decreased from good to poor.SRH is an important predictor for poor functioning in diabetes, but the trajectory of SRH seems to be even more important. Health professionals should pay attention to not only SRH per se, but also changes in SRH over time.  Diabetes is a chronic condition associated with reduced physical functioning . There iSelf-rated health (SRH) is a single-item measure that is one of the most widely used measures of general health in population health research. The most commonly used form asks people to characterize their health as excellent, very good, good, fair, or poor. SRH has received strong support as an independent predictor of morbidity, disability, health service utilization and mortality ,4, even Although it is well known that SRH is a dynamic perception of health status that changes over time , relativThe aims of the present paper were to: (1) determine whether a set of SRH trajectories can be identified in a community sample of people with diabetes; (2) describe sociodemographic and clinical characteristics associated with these trajectories; and (3) examine the effect of different trajectories of SRH on functioning outcome. Identification of trajectory groups of SRH may provide a deeper understanding of SRH as a risk factor for variation in health outcomes in people with diabetes and might help identifying high risk groups in this population. The Douglas Mental Health University Institute Ethics Board approved the consent procedures and the study protocol. All participants gave oral informed consent prior to their inclusion in the study. Oral consent was documented by the interviewer.We used data from the longitudinal Montreal Diabetes Health and Well Being Study (DHS). The DHS is a community based telephone survey of adults with self-reported diabetes in Quebec, Canada. Participants were recruited by a recognized polling firm  between January 2008 and April 2008 through random selection of phone numbers. Interviews were conducted in English and French by trained professional interviewers using a computer-assisted telephone interview system .The sampling frame consisted of all households with a listed telephone number in Quebec, Canada. Eligible participants were individuals who were between 18 and 80 years of age and had a diagnosis of type 1 or type 2 diabetes. Four follow-up interviews were conducted approximately 12, 24, 36 and 48 months after baseline interview (late winter/early spring). More details from the baseline assessment are published elsewhere . SRH was assessed with one item: “Would you say that in general your health is…” Participants were asked to answer with a 5-category Likert response scale . We used the coding suggested by Diehr et al. , with 95Global functioning was assessed using the 12-item version of the World Health Organization Disability Assessment Schedule II (WHO-DAS-II) . The WHOThe Patient Health Questionnaire (PHQ-9) -24 was uParticipants with age at diagnosis < 30 years and insulin use immediately after diagnosis were epidemiologically classified as having type 1 diabetes, while other participants were classified as having type 2 diabetes. To identify distinct trajectories of self-reported health , we used trajectory modeling ,29. We uIn the ‘proc traj’ macro, subjects do not need complete data for all four assessment points to be included in the analysis. Missing data are assumed to be missing at random. We compared prevalence of sociodemographic variables and baseline health characteristics by trajectory group .The derived trajectory groups (from baseline to three years follow-up) were subsequently compared at 4 years follow-up with respect to functioning. Logistic regression analysis was conducted to compare the risk of poor functioning for the different trajectories while controlling for potentially confounding variables, including poor functioning history, depression history, complications history, type of diabetes, duration of diabetes, age, sex, and education. Contrasts were used to determine whether disability differed between the trajectories groups.A total of 2003 individuals with type 1 or type 2-diabetes participated in the DHS at baseline . After excluding those who refused to participate in a follow-up interview (n=246), 1757 individuals formed the baseline sample for the longitudinal cohort. The number of participants with complete information on SRH at baseline and the three follow up interviews was 1746, 1287, 1142 and 1144, respectively. The number of deceased participants at the three follow-up interviews was 32, 17 and 12, respectively. For the trajectory analysis, we included participants who a) had complete information on SRH at baseline and b) participated in at least two follow up interviews or were deceased. A total of 1288 people had complete information on SRH in at least two follow-up assessments and 948 of those participants participated in the four years follow-up assessment.The participants and those who dropped out did not differ in SRH scores at baseline and follow-ups. Participants who dropped out had poorer functioning status (p<0.001), more diabetes specific complications (p<0.001) and suffered more often from depressive symptoms (p<0.001) at baseline than those who did not drop out. Mean SRH scores decreased minimally over time: the scores for baseline and the three follow-up assessments were 71.8 (SD=24.2), 71.2 (SD=25.8), 68.6 (SD=27.8) and 68.5 (SD=28.4), respectively. Four distinct trajectories of SRH were identified: (1) persistently poor self-rated health ; (2) progressively increased self-rated health ; (3) progressively decreased self-rated health ; and (4) persistently good self-rated health . The results of the trajectory analysis are presented in The mean posterior probability value of each group in the four-group model was 0.96 or higher. Sociodemographic and clinical baseline characteristics are presented in At three years follow-up assessment, 79.3% of participants in the P-SRH group had a history of depressive symptoms (baseline to three years follow up). Rates of depression history for the I-SRH, D-SRH and G-SRH groups were 57.3%, 67.4 %, and 27.9 %, respectively. Rates of poor functioning history were 86.7%, 68.9%, 82.6% and 24.4% for participants in the P-SRH, I-SRH, D-SRH and G-SRH groups, respectively.In sensitivity analyses we repeated our analyses for participants with complete SRH information at all three follow-up assessments. In these analyses, the number of groups and group characteristics did not differ systematically. In this prospective community study of people with diabetes, we have identified four distinct trajectories of SRH over a three-year period. The vast majority of the study participants had no major change of SRH status over the course of three years: 72 % were assigned to a persistently good SRH trajectory, while 10% were assigned to a persistently poor SRH trajectory. In contrast, perception of health status changed for the other two groups: one group changed from good to poor SRH, while the other group changed from poor to medium/good SRH. Our study adds to the current literature in three ways. First, we have evaluated short-term change of SRH in community sample of people with a chronic condition (diabetes), rather than evaluating long-term change of the SRH in a general population sample. Second, using trajectory modeling, we have identified one subgroup of participants with an improved self-rated perception over time. Most of the previous prospective studies on the course of SRH in community based samples have identified stable or decreasing trajectories of SRH ,31-33. OThird, we found that SRH history might be a better predictor for poor functioning than a single assessment of SRH. For example, the progressively decreased SRH group and the persistently poor SRH group had similar poor SRH scores at three years follow-up assessment, but the risk of poor functioning at four years follow-up was different: those with a persistent poor perception of health status were at higher risk for poor functioning than the other group where health perception changed over time, even after controlling for poor functioning history and other potentially confounding variables. Furthermore, the two groups with changing health perception over time - D-SRH and I-SRH - had different SRH scores at three years follow-up, but both groups had a similar risk for poor functioning at the 4-year follow up. SRH is a widely used measure; the usefulness of this single question is well established ,34. NeveThe SRH measure is often dichotomized into two categories (fair/poor vs. excellent/very good/good) in epidemiological research. In the present study we used a coding suggested by Diehr et al.  which caA limitation of this coding, as well as of the SRH measure, is the lack of medium health category. The role of SRH as a risk factor for poor health outcomes has been shown in the literature ,36, althThe study has limitations. SRH is a very brief measure and its longitudinal validity is threatened by ceiling effects (people in the highest category of SRH cannot improve). The PHQ-9 and the WHO-DAS-II are brief questionnaires for the assessment of depression and functioning. Functioning is complex, multi-dimensional phenomenon and a global self-report instrument might not cover all aspects of functioning. Furthermore, we have no information about functioning history before baseline and between follow-up assessments. We also have no information on clinical parameters like blood glucose levels. Another limitation is that our other study variables were self-reported and taken at one point in time, which may not fully capture a person’s life-time experiences. The sampling frame was limited to those with landline telephones, which might result in selection bias. Attrition might be another source of bias, although there was no evidence of different SRH scores in those lost to follow-up. Finally, our findings may not be valid for people with undiagnosed diabetes.In conclusion, our results confirm that current SRH is an important predictor for disability in diabetes, but the trajectory of SRH seems to be even more important. Health professionals should pay attention not only to SRH per se, but also changes in SRH over time  among people with diabetes. A decline in SRH over time indicates that health status is deteriorating and that there is also an increased risk of poor functioning.


They showed little effect against type 2a polymerase. One of the compounds, G05, was selected and further characterized. It inhibited the synthesis of RNA by recombinant HCV NS5B polymerase in a dose dependent manner. The CC50 value was 77 μM. The inhibition was in a noncompetitive manner with the substrate UTP. The compound did not inhibit the elongation step of RNA synthesis in a single-cycle processive polymerization assay. It inhibited the binding of NS5B polymerase to the template RNA in a dose-dependent manner.In an effort to find chemicals inhibiting the enzymatic activity of the hepatitis C virus (HCV) NS5B polymerase, a series of thiobarbituric acid derivatives were selected from a library provided by Korea Research Institute of Chemical Technology and characterized. The selected compounds exhibited IC The hepatitis C virus causes chronic hepatitis in human, and an estimated 170 million people are infected worldwide . HoweverNonstructural protein 5B is responsible for HCV genomic replication , which mWhile screening a chemical library provided by Korea Research Institute of Chemical Technology, several thiobarbituric acid derivatives were found by the current authors to have inhibitory effects on the HCV NS5B polymerase. This study reports on the characterization of inhibitory mechanism by the compounds.32P]-UMP incorporation assay with a purified recombinant NS5B and poly(A)-oligo(dT) template. Potent inhibition against 1b type polymerase (Con-1) was exhibited with IC50 values between 1.7 and 3.8 μM. But essentially no inhibition was observed against 2a (JFH-1) type polymerase. The inhibitory effects on the 1b type HCV subgenomic RNA replicon -UTP, and 50 μM UTP for the polymerization reaction. Thereafter, the G05 compound was added and the reaction mixture was further incubated and visualized after running on a polyacrylamide gel. Since the nucleotide mixture was added along with heparin, the level of RNA synthesis could only be measured from the preformed template-enzyme complex. In the presence of an increasing concentration of the G05 compound, the amount of newly synthesized RNA did not change -oligo(dT) template and recombinant NS5B and represents the concentration of the inhibitor showing a 50% reduction in the recombinant NS5B polymerase activity. Unit = μM. # The EC50 was measured by real-time RT-PCR analysis and represents the concentration of the inhibitor showing 50% reduction in the RNA level in a Huh7 cell harboring the HCV subgenomic replicon. Unit = μM.Click here for file


Recent advancement in genomic and genetic sequencing technology has ushered in a new era in which unprecedented amount of genomic sequence and transcript sequence data with extraordinary detail can be generated at incredibly short time. As part of this advancement, the approaches that utilize the powerful next generation sequencing technology, such as RNA-Seq, may have dramatically changed the field of non-coding RNA (ncRNA) research. Since these new approaches do not require prior knowledge of annotated transcripts for probes, theoretically the entire transcriptome of a given sample can be sequenced. This enables the detection of novel transcripts, including both protein coding and ncRNA, as well as RNA with somatic mutations and alternative splicing forms  bases in the human genome are transcribed into genes that code for proteins , which is believed to be the transcripts of 1–3% of the human genome. miRNA is highly involved in brain development and plasticity at the neuronal level (Kapsimali et al., de novo gene mutations also provides valuable and necessary tools for the addiction research field.A much less tapped area in ncRNA research for the understanding of addiction of cocaine, or other substances of abuse, is the lncRNA; Wapinski and Chang, The complexity and abundance of ncRNA, especially lncRNA, mandate advanced non-traditional, large scale and high throughput transcript sequencing, and analysis. While microarray technology enjoys established base and proven utility, the next generation sequencing technology represented by RNA-Seq emerges as the future choice approach for the task because of its unbiased coverage of the entire transcriptome of the genome. In addition, RNA-Seq allows versatile experimental design for sequencing depth and adjustable detection sensitivity, using machines of different throughputs and multiplexing different numbers of samples on a sequencing lane. Furthermore, the inherited benefit of RNA-Seq (Mane et al.,


The genomic information which is transcribed into the primary RNA can be altered by RNA editing at the transcriptional or post-transcriptional level, which provides an effective way to create transcript diversity in an organism. Altering can occur through substitutional RNA editing or via the insertion or deletion of nucleotides relative to the original template. Taking advantage of recent high throughput sequencing technology combined with bioinformatics tools, several groups have recently studied the genome-wide substitutional RNA editing profiles in human. However, while insertional/deletional (indel) RNA editing is well known in several lower species, only very scarce evidence supports the existence of insertional editing events in higher organisms such as human, and no previous work has specifically focused on indel differences between RNA and their matching DNA in human. Here, we provide the first study to examine the possibility of genome-wide indel RNA-DNA differences in one human individual, NA12878, whose RNA and matching genome have been deeply sequenced.We apply different computational tools that are capable of identifying indel differences between RNA reads and the matching reference genome and we initially find hundreds of such indel candidates. However, with careful further analysis and filtering, we conclude that all candidates are false-positives created by splice junctions, paralog sequences, diploid alleles, and known genomic indel variations.Overall, our study suggests that indel RNA editing events are unlikely to exist broadly in the human transcriptome and emphasizes the necessity of a robust computational filter pipeline to obtain high confidence RNA-DNA difference results when analyzing high throughput sequencing data as suggested in the recent genome-wide RNA editing studies. RNA is an important biomolecule that is deeply involved in almost all aspects of molecular biology, such as protein production, gene regulation, and viral replication. In ordeThe most common type of known RNA editing in metazoans involves conversion of adenosine to inosine (A-to-I editing), which iTaking advantage of whole-genome and transcriptome deep-sequencing technologies, recent studies have extensively investigated all the potential types of substitutional RNA editing in the human transcriptome using bioinformatics tools that are capable of identifying mismatches between RNA reads and the matching reference genome-17. WhilMyxomycota[Physarum[et al.[Insertional and deletional editing events have been discovered in various species,4, such yxomycota. Most ofyxomycota, creatinyxomycota and Phys[Physarum mitochon[Physarum. In highum[et al. reportedIn this study, we explore the possibility of indel RNA editing events across the transcriptome in human by systematically examining the variations between RNA-seq reads and their matching genome. Specifically, we examine the possibility of genome-wide indel RNA-DNA differences in one human individual, NA12878. We apply different computational tools that use gapped alignments to identify indel differences between RNA reads and the matching genome. While hundreds of such indel candidates are revealed after initial selection, further analysis and filtering indicate that all of them are false positives which result from incorrect alignments including splice junctions, paralog sequences, diploid alleles, and known genomic indel variations. The results from our study suggest that indel RNA editing events are unlikely to exist widely in the human transcriptome and emphasize the importance of thorough filtering in genome-wide studies of RNA editing.Figure The initial step in the detection of RNA-DNA differences is the accurate mapping of RNA-seq reads to their matching reference genome. Failure to correctly assign a read to its original location may lead to spurious alignments that may be misinterpreted as editing events. Since a large number of genomic variations including single nucleotide differences and indels exist among different individuals, it is crucial to compare RNA and DNA sequences from the same background . Based on the reference genome (NCBI build 36) and incorporating genomic variations and structural variations identified by the 1000 Genome pilot project, the GerThe rapid emergence of high-throughput sequencing techniques has resulted in the development of a variety of short sequence read mappers that are based on different alignment strategies. Since our goal is to identify indels within all RNA-DNA differences events, the basic requirement for the mapping tools is that indels should be allowed when aligning short RNA reads to the reference. By evaluating most of the currently available mapping tools, we find that BFAST (Blat-like Fast Accurate Search Tool) is one oFor the initial BFAST mapping , out of the 113,902,864 reads, 79,833,200 could be mapped to the assembled maternal haploid genome of GM12878 over their entire length. For bowtie2  a total of 40,862,987 reads could be mapped to the assembled maternal genome over their entire length. This mapping ratio is significantly lower than that in BFAST, which is probably due to the higher stringency of bowtie2 for mapping a read to the reference genome.The mapping output for BFAST and bowtie2 are SAM (Sequence Alignment/Map) files, which were processed by the SAMtools software package, a packaAfter these initial selections, 685 candidates remain in the BFAST results while 250 candidates remain in the bowtie2 results. Of these, 110 were shared between the two mapping approaches. The fact that bowtie2 has much fewer candidates than BFAST is probably due to the lower read mapping ratio mentioned above. As for the candidates found by bowtie2 but not by BFAST, many are at the edge of the filtering thresholds. Thus, small differences in the way quality measures and variants of aligned reads are reported in the two mappers lead to a candidate being just above the threshold in one method and just below in the other. We notice, that as indicated below all these questionable reads are filtered out by the additional false positive filtering steps and the overlap between remaining candidates based on BFAST alignments and remaining candidates based on bowtie2 alignments is much larger.After the initial selections, the list of indel variations called by SAMtools may still contain a large number of false positives that are unrelated to indel RNA editing. These false positives may be a result of known genomic variations, different alleles from diploid genomes, and misalignment of reads due to, e.g., splice junctions and paralog sequences in the genome. We thus apply a series of stringent filters to remove false positives from our candidate lists.Since we initially aligned RNA-seq reads to the maternal genome, we first check if the candidate indel RNA-DNA differences result from genuine maternal-paternal genome differences by realigning all the reads that can be mapped to the putative indel sites  to the paternal genome using BFAST. This filter identifies 45 sites in the BFAST dataset as well as 60 in the bowtie2 dataset that reflect genuine maternal-paternal genome variations where the apparent indels in the RNA-seq reads reflect the paternal RNA transcript form  Only part of the sequence from the genome version can be properly aligned without indels to one of the RNA sequences in the splice junction database (this RNA sequence corresponds to the same position in the reference genome as found in (1), but contains a splice junction close to the putative indel site); (3) The surrounding sequence which includes the indel can be fully aligned to the same splice junction RNA sequence identified in (2) without any gaps ;  The surrAs suggested in, potentiAfter eliminating false positives from incorrect alignment in the same individual described above, only 12 candidates remain in the BFAST dataset  44 sites are found when using the maternal genome for indel calling (where we excluded sites with homopolymer runs of greater than 5 bp which have a higher chance to result from sequencing errors rather than true indel differences). If indel calls from alignments to the maternal and the paternal genome are combined, we found nearly 90% of the covered genomic indels. We thus conclude that the lack of indel editing sites found in our study is not due to a lack in sensitivity of the pipeline.In order to study the dependence of these results on technical details such as read length, we examine other RNA-seq data sets from a recent study on the sIn this work, we provide the first systematic study of the possibility of genome-wide indel RNA-DNA differences in one human individual, NA12878, whose RNA and matching genome have been deeply sequenced. We applied different computational tools that are capable of identifying indel differences between RNA reads and the matching reference genome. After initial selection using SAMtools, we found hundreds of such indel candidates. However, with careful further analysis and filtering, we found that all of them are false-positive results such as splice junctions, paralog sequences, different alleles from diploid genomes, and known genomic indel variations from the SNP database. We thus conclude that there is no evidence for widespread insertional or deletional RNA editing in the human genome.However, it should be noticed that the RNA-seq data sets we used are from a particular lymphoblastoid cell line; it is thus in principle still possible that widespread indel RNA editing events could be cell type specific and that we may have missed them by selectively focusing on the lymphoblastoid cell line. Moreover, our stringent requirement for detecting such events  may have missed potential sites which are edited at very low frequency.It is interesting to relate our findings to the recent discussions on substitutional RNA editing initiated by Li et al.. SeveralThe absence of indel RNA editing in our study also has to be discussed in the light of the previous study suggesting two potential insertional RNA editing sites in human. This aph1.0, 11 of 301 EST sequences support the “edited” version; while for hmgn1, only one EST sequence supports the “edited” version).First, as mentioned above, the editing events may not occur in the specific cell line we investigated. Moreover, the study in showed tHowever, the results of our filtering analysis promote us to also consider the possibility that these apparent “insertional editing sites” could be signatures of other biological “artifacts”, such as a paralog sequence or splice junction. We thus examined if these sites could result from paralog sequences in the genome but found no such paralog sequence. However, when examining the EST data which were used as evidence for editing sites  as the one used for assembly of the diploid genome sequences of the individual NA12878 were downloaded from the NCBI Sequence Read Archive (SRA). In order to verify the robustness of our results with respect to sequencing parameters such as read length, other single end RNA-seq datasets were downloaded from NCBI GEO (GEO accession number GSE30401). The latter RNA-Seq data sets were generated as part of the ENCODE Project[The assembled diploid genome sequences of the individual NA12878, genome annotations and corresponding variants information  were downloaded from Project. Table RNA-seq reads were first aligned to the maternal-derived haploid genome sequences using the standard pipeline of the Blat-like Fast Accurate Search Tool (BFAST). As one Most of the parameters in the alignment process were set to their default values. A single lookup is ignored if it returns more than K=8 candidate alignment locations (CALs); the maximum number of CALs for a read was M=1280. Local alignments were performed for each CAL using default settings and nucleotide substitutions, insertions and deletions were identified in the gapped alignment. Alignments were prioritized by alignment score and only the highest scoring alignment for each mapping read was output. The mapping output was set to SAM format.http://samtools.sourceforge.net/) for variant calling. The version we used in this study was samtools.0.1.17.To identify RNA editing sites, the output RNA-seq alignment files in SAM format were processed by the publicly available, open source SAMTools software package  and then these BAM files were sorted and indexed for rapid lookup. The sorted BAM files were further processed in the variant calling step: using the “mpileup” function in SAMTools, indexed reference sequences and position sorted bam alignment files generated files with read information at sites where mismatches and indels from the reference sequence were detected. Then, only information for indel differences was kept, while reads that contained only mismatches were discarded. The output file after this step served as the starting dataset for the indel RNA editing analysis.To eliminate false positive results due to sequencing and reverse transcription errors, the initially identified indel variants were further filtered by the following criteria:1. Base quality filter: remove bases at the indel site with a sequencing quality score below 20.2. Mapping quality filter: remove reads with a mapping quality score below 20; discard a read if the indel position is within 2bp of the 5' end or 3' end; discard an indel-containing read if more than 3 mismatches are present.3. Coverage depth filter: remove candidates with less than 2 indel-containing nonduplicated reads; remove candidates with less than 5 reads; remove candidates with less than 5% indel-containing reads of the total covering reads.4. Variant quality: remove candidates with QUAL Phred-score of variant calling below 0.01.5. Indel type and size filter: remove variant sites that display more than one nonreference alleles as well as variant sites that contain any uncertain bases (“N”); only keep candidates with only one nucleotide difference from the genomic DNA ; remove variant sites that display homopolymer runs of more than 5 identical nucleotides.BLAST: Basic local aignment search tool; BFAST: Blat-like fast accurate search tool; NCBI: National center for biotechnology information; RNA-seq: RNA sequencing; SAM: Sequence alignment/map; SNP: Single-nucleotide polymorphism; SRA: Sequence read archive.The authors declare that they have no competing interests.CC was involved in the conception of the study, performed all the computational work, and drafted most of the manuscript. RB conceived and directed the study and revised the manuscript into its final form. All authors read and approved the final manuscript.


Purpose of Study. Diagnosis of prosthetic loosening in hip and knee arthroplasty remains a challenge. Although there are a number of diagnostic tools, no single test or combination is 100% sensitive or specific. There has been a recent interest in the use of radionuclide arthrography (RNA) for detection of prosthetic loosening. Methods. A retrospective review of 45 consecutive RNA scans from 2005 to 2010 was conducted. RNA findings were compared with intraoperative findings at revision and/or serial radiographic examinations to confirm loosening. A component was considered loose if sequential radiographs demonstrated macromotion, gross subsidence, or progressive radiolucency. Results. There were 26 females and 17 males, with mean age at RNA of 71 years (range of 53–89 years) and mean time from index surgery, 6.4 years (range of 0.5–23 years). There were 23 total knee replacements (TKR) (19 primary and 4 revision) and 20 total hip replacements (THR) (11 primary and 9 revision). 15 patients underwent revision surgery following RNA. Strict inclusion criteria allowed 27 patients for further analysis. Sixteen RNA scans were suggestive of loosening, of which 14 were confirmed loose. Eleven scans were suggestive of a stable prosthesis, of which 10 were confirmed well fixed. RNA had a sensitivity of 93%, specificity of 83%, positive predictive value of 88%, and negative predictive value of 91%. Conclusion. Radionuclide arthrography should be considered a useful adjunct in the diagnosis of prosthetic loosening in the challenging patient. The incidence of prosthetic loosening is increasing with the growing number of hip and knee arthroplasty –3. In AuThe diagnosis of prosthetic loosening remains a challenge for the treating clinician, particularly differentiating between septic and aseptic prosthesis loosening , 5–8. AtOR, serial radiological follow-up (an index X-ray of the implant at the time of RNA and at least 2 further radiographs at 6 m and 12 m after RNA). Patients were also required to have either a TKR or THR.A retrospective review at the Queen Elizabeth Hospital in Adelaide, south Australia, identified 45 consecutive RNA scans performed from January 2005 to April 2010, which encompassed all RNA scans during this period. These scans were performed to investigate suspected loosening of knee or hip arthroplasty. In order to confirm the validity of the RNA result, the following inclusion criteria were required: revision surgery within 1 year of the RNA, Sixteen patients were excluded due to insufficient radiological follow-up, where no serial radiographs could be identified. A further 2 patients were excluded with hemi-arthroplasties.This left a total of 27 patients for analysis. Twelve RNA scans were compared to revision findings at surgery (44%), and 15 were compared to radiograph series (56%). RNA technique was carried out under fluoroscopic guidance and aseptic conditions. An 18-gauge needle was inserted laterally between the femoral condyle and the patella into the knee joint space and a lateral approach to the hip joint. A small amount of contrast was injected if necessary to confirm appropriate positioning before the colloid injection . 50 MBq Anterior, posterior, medial, and lateral images of the knees and anterior, posterior, lateral, anterior oblique, and posterior oblique images of the hips were obtained approximately 30 min and 4 h after injection. The patient was encouraged to ambulate between imaging times. Further images were obtained at 24 h if necessary to obtain a good tracer image . LooseniEach RNA scan was classified into “positive” or “negative” for loosening. Classification was determined based on interpretation by a nuclear medicine specialist and the subsequent RNA report. Each patients' radiograph series or revision findings were classified into “loosening confirmed” or “arthroplasty stable.” Loosening on radiograph series was confirmed separately by 2 orthopaedic fellows. A component was considered loose if sequential radiographs demonstrated macromotion, gross subsidence, or progressive radiolucency of >2 mm at interfaces. Classification described by Harris et al. was utilized for femoral component loosening . LooseniA total of 27 patients were included in the analysis. There were 16 females and 11 males, with a mean age of 71 years. The mean time from index surgery to RNA was 6.5 years, with a range of 6 months to 23 years. There were 13 TKR and 14 total THR. Of the 13 TKR, 11 were primary replacements and 2 were revisions, 3 were cemented, 5 were uncemented and 5 were hybridised. Of the 14 THR, 8 were primary replacements and 6 were revisions, 4 were cemented, 3 were uncemented, and 7 were hybridised with a cemented stem and uncemented cup.Twelve RNA scans were compared to revision findings at surgery (44%), and 15 were compared to radiograph series (56%). There were 16 positive RNA results. Of these, 14 were confirmed loose by radiograph series or revision findings, and 2 were confirmed stable. There were 11 negative RNA results. Of these, 10 were confirmed stable and 1 was confirmed loose see .This gave a true positive of 14 out of 16 results and a true negative of 10 out of 11 results. The calculated sensitivity of RNA in our study was 93%. The calculated specificity was 83%. Sensitivity was calculated as True positives/. Specificity was calculated as True negatives/.The positive predictive value (PPV) and negative predictive value (NPV) are 88% and 91%, respectively.There are a number of tools available to the orthopaedic surgeon for the diagnosis of prosthesis loosening; however, no single tool or combination of tools has been found to be 100% sensitive or specific . AvailabIn recent years, RNA has been used at our institution as an adjunct in the diagnosis of prosthetic loosening. The aim of this study was to determine if it added value to the standard workup of such patients. In 2006, Temmerman et al. reported a sensitivity of 69% and a specificity of 76% for nuclear arthrography and concluded that, when used in conjunction with plain radiography, it made a significant contribution to the diagnosis . A similLimitations of this study include the limited sample size and the selection of patients for which RNA is typically used in our institution. Our limited sample size will alter the accuracy of sensitivity, specificity, PPV, and NPV, and larger studies are needed to provide support to these results. In addition, patients selected for RNA are typically those who have a history suggestive of loosening, with clinical examination, plain radiograph, and whole body bone scan (WBBS) unable to provide a definitive diagnosis. Unfortunately this means that no RNA research had yet been produced as a first-line detection modality on a randomised group of patients with TKR or THR.Another limitation to the study design is the use of plain radiograph series or revision operative findings as a gold standard to compare with the accuracy of RNA. The sensitivity and specificity of serial radiographs are limited, with some reports suggesting varied sensitivities of between 85% and 95% –18. In sA known concern of RNA as a diagnostic tool is the potential to introduce infection into the joint space. At our institution, however, there has not been a single reported incidence of this complication from the 45 RNA studies surveyed between 2005 and 2010. RNA requires specialised training in correct administration technique and analysis of images retrieved as it is not a mainstream modality. Currently, there is a lack of standard criteria for interpretation of RNA, and hence this may result in poor reproducibility of RNA results. This study highlights the need for the development of diagnostic criteria, which will allow the wider use of RNA and more consistent interpretation of results.A potential advantage that RNA may offer is the option of concurrent synovial aspiration in cases with a potential infectious aetiology. We recommend this as a routine additional diagnostic tool. Future potential for RNA has also been mentioned in combination with the newer SPECT or SPECT/CT technology, which allows for 3D images to be taken of the joint and is used concurrently with identification of RNA tracer leakage. In a recently published article, Chew et al. discuss the emerging applications of this technology .There may be additional cost benefits associated with RNA in the decision to delay or not proceed with revision surgery if a finding negative of loosening is reported. However, no cost versus benefit data is available at this time and is highly institution specific.We conclude that RNA should be considered as an additional diagnostic tool for use in difficult cases of suspected prosthetic loosening and that it is a safe and effective diagnostic modality with high accuracy. Further studies with larger numbers of patients and follow-up will be required to define a standardised criterion for its interpretation.


Escherichia coli possesses a number of proteins that transport sugars out of the cell. We identified 31 candidate sugar efflux transporters based on their similarity to known sugar efflux transporters. We then tested whether these transporters affect arabinose and xylose metabolism. We identified 13 transporters – setC, cmr, ynfM, mdtD, yfcJ, yhhS, emrD, ydhC, ydeA, ybdA, ydeE, mhpT, and kgtP – that appeared to increase or decrease intracellular arabinose concentrations when respectively deleted or over-expressed. None of the candidate transporters affected xylose concentrations. These results indicate that E. coli possesses multiple arabinose efflux transporters. They also provide a novel target for future metabolic engineering. Escherichia coli expresses proteins that not only transport sugars into cells but also a number of proteins that transport them out of the cell. The canonical example is the SET family of transporters: SetA, SetB, and SetC Efflux transporters have been extensively studied in the literature in the context of multi-drug resistance (MDR). Little is known about these sugar efflux transporters, or what roles they may play in cellular metabolism. One possible mechanism is to relieve sugar-phosphate stress. Sun and Vanderpool demonstrated that SetA participates in the glucose-phosphate stress response E. coli. Sequence analysis identified 31 candidate sugar efflux transporters in E. coli based on homology to known sugar efflux transporters. Using genetic approaches, we tested whether these candidate efflux transporters target arabinose and xylose. We were able to identify multiple putative arabinose efflux transporters but interestingly none for xylose.In this work, we investigated L-arabinose and D-xylose  efflux in E. coli based on homology to the known sugar efflux transporters: ydeA, setA, and setB .We identified 31 candidate sugar efflux transporters in and setB Table 1.araBAD promoter to Venus, a fast-folding variant of the yellow fluorescent protein araBAD promoter as determined using fluorescence is proportional to extracellular arabinose concentrations and presumably relative intracellular arabinose concentrations as well based on the known mechanism for regulation araBAD promoter activities. The resulting data were fit to a Michaelis-Menten dose-response curve with the governing parameters, Vmax and Km, reported ; 2) phosphorylation to L-ribulose-5-phosphate (araB); and 3) inversion to D-xylulose-5-phosphate (araD). We tested three mutants: ΔaraA, ΔaraB, and ΔaraBAD. We did not test a ΔaraD mutant as arabinose is toxic in this strain.The arabinose metabolic intermediate, L-ribulose-5-phosphate, is toxic to setC, mhpT, cmr, ynfM, mdtD, yfcJ, yhhS, and emrD were deleted as well (data not shown). These results suggest that arabinose concentrations are already high in these cells and eliminating efflux does not further increase arabinose concentration. Therefore, we were unable to conclude anything from these deletion experiments.Blocking any step in arabinose metabolism significantly increased the concentration of intracellular arabinose relative to the wild-type control. This is expected, as arabinose is no longer being metabolized in any of these strains. However, we did not observe any further increase when setC, ydeE, and ydeA was most pronounced in a ΔaraA mutant, indicating that the three target arabinose . Aside from TolC, these candidate efflux transporters may associate with other proteins that were not considered in our analysis. If this is the case, then the over-expression studies may have missed some efflux transporters as the accessory proteins would not be expressed in the correct stoichiometry for these over-expressed transporters to be functional.Many efflux transporters are TolC dependent A number of the identified efflux transporters have previously been shown to transport other compounds both in and out of the cell. Cmr, for example, is known to efflux a number of chemically unrelated compounds E. coli want to efflux arabinose from the cell? One possibility is to limit the accumulation of toxic sugar phosphates, such as the arabinose metabolic intermediate L-ribulose-5-phosphate, within the cell. If the flux of arabinose is greater than the pentose phosphate pathway can accommodate, then L-ribulose-5-phosphate may accumulate within the cell due to an effective roadblock within the pathway. Under such a scenario, arabinose efflux transporters would provide a relief valve for the cell. A second possibility is to limit the accumulation of methylglyoxal, another toxic compound to E. coliWhy would marRAB operon involved in antibiotic resistance. Whether arabinose and other sugars activate the MDR regulators is not known though it is an intriguing hypothesis nonetheless.Other outstanding questions concern the regulation of these transporters. Arabinose was found to induce the expression of many efflux transporters, where the effects were most pronounced for the YdeA and YhhS transporters. We and others have previously speculated that the multidrug antibiotic resistance (MDR) mechanisms in bacteria evolved in part as a mechanism to prevent the buildup of toxic metabolites E. coli. Of course, naively removing these transporters may have a detrimental effect on the cell due to the buildup of toxic metabolites. Any design targeting efflux may also need to make commensurate changes to transport and metabolism. Whether sugar efflux transporters provide a viable target for metabolic engineering is not known, but it does provide a totally unexplored area that clearly merits further investigation.We conclude by noting that sugar efflux may provide a novel target for metabolic engineering. In particular, one may be able to increase the metabolic flux through a given pathway by eliminating the efflux of the governing sugar. The present work was motivated in part by looking at novel targets for optimizing pentose metabolism in °C. Antibiotics were used at the following concentrations: ampicillin at 100 µg/ml, chloramphenicol at 20 µg/ml, and kanamycin at 40 µg/ml. Inducer isopropyl-β-D-galactopyranoside (IPTG) was used at a concentration of 2 mM unless otherwise specified. All experiments involving the growth of cells carrying the helper plasmid pKD46 were performed at 30°C. Loss of pKD46 was achieved by growth at 42°C under nonselective conditions on LB agar. The removal of the antibiotic cassette from the FLP recombinant target (FRT)-chloramphenicol/kanamycin-FRT insert was obtained by the transformation of the helper plasmid pCP20 into the respective strain and selection on ampicillin at 30°C. Loss of pCP20 was obtained by growth at 42°C under nonselective conditions on LB agar. Primers were purchased from IDT, Inc. Enzymes were purchased from New England Biolabs and Fermentas.Luria-Bertani liquid and solid medium  was used for routine bacterial culture and genetic manipulation. All experiments were performed in tryptone broth at 37 and Escherichia coli K-12 strain MG1655. All cloning steps were performed in E. coli strain DH5α (phi-80d lacΔm15 enda1 recA1 hsdR17 supE44 thh-1 gyrA96 relAΔlacU169). Targeted gene deletions and subsequent marker removal were made using the λRed recombinase method of Datsenko and Wanner vir was used in all genetic crosses according to standard methods Bacterial strains and plasmids used in this study are described in vir transduction.The plasmids pKD3 and pKD4 were used as templates to generate scarred FRT mutants as previously described. Mutations were checked by PCR using primers that bound outside the deleted region. Prior to the removal of the antibiotic resistance marker, the constructs resulting from this procedure were moved into a clean wild-type background by P1venus was constructed by digesting the plasmid pQE80L-venus by EcoRI and NheI and cloning the fragment into pPROBE-gfp[tagless] digested by EcoRI and NheI. This replaced the gfp[tagless] by the fast-folding yfp variant Venus in pPROBE venus . The araBAD promoter was amplified using primers TD088f (sequence: 5′-G GTA CCC ATT CCC AGC GGT CG GGA AA) and TD088r (sequence: 5′-G AAT TCG CCA AAA TCG AGG CC GAC TA). The xylA promoter was amplified using primers TD065f (sequence: 5′-G GTA CCT CGA TCT TTT TGC CA GGA AA) and TD065r (5′-G AAT TCG CGA TCG AGC TGG TC GAC TA). The PCR fragments were then digested with KpnI and EcoRI (sequences underlined) and cloned into the multiple cloning site of the pPROBE-venus vector. The resulting transcriptional fusions were transformed into the mutated strains containing the deletions of interest.The plasmid pPROBE-trcPlasmids overexpressing the genes of interest were constructed by cloning the respective gene into the multiple cloning site of pTrc99A under the control of a strong IPTG inducible promoter, P600) were measured. The fluorescence readings were normalized with the OD600 to account for cell density. All experiments were conducted in triplicates and average values with the standard deviations are reported.End-point measurements of the fluorescent reporter system were made using a Tecan Safire 2 microplate reader. 3 mL cultures were grown overnight in tryptone media at 37°C and then subcultured 1∶30 after which 0.45 mL was transferred to a single well of a polypropylene, 2.2 ml, deep, square, 96-well microtiter plate . Cultures were then grown at 37°C while shaking at 600 rpm on a microplate shaker (VWR). After an optical density of 0.05 was reached, the cells were induced with varying concentrations of the sugar of interest (either arabinose or xylose). Extracellular sugar concentrations ranged from 1 mM to 10 mM. In addition, strains containing the expression plasmids for the genes of interest were also induced with IPTG. Final volumes in each well were adjusted to 0.5 mL for all cultures. When the cells reached an OD of 0.4–0.5, 100 µL of the culture was transferred from the deep-well plates to black, clear-bottomed Costar 96-well microtiter plates, and the fluorescence (excitation/emission λ, 515/530 nm and OD at 600 nm (OD


We have previously reported that the mitochondria inhibitor 3-nitropropionic acid (3-NP), induces the expression of DNA damage-regulated autophagy modulator1 (DRAM1) and activation of autophagy in rat striatum. Although the role of DRAM1 in autophagy has been previously characterized, the detailed mechanism by which DRAM1 regulates autophagy activity has not been fully understood. The present study investigated the role of DRAM1 in regulating autophagy flux. In A549 cells expressing wilt-type TP53, 3-NP increased the protein levels of DRAM1 and LC3-II, whereas decreased the levels of SQSTM1 (sequestosome 1). The increase in LC3-II and decrease in SQSTM1 were blocked by the autophagy inhibitor 3-methyl-adenine. Lack of TP53 or knock-down of TP53 in cells impaired the induction of DRAM1. Knock-down of DRAM1 with siRNA significantly reduced 3-NP-induced upregulation of LC3-II and downregulation of SQSTM1, indicating DRAM1 contributes to autophagy activation. Knock-down of DRAM1 robustly decreased rate of disappearance of induced autophagosomes, increased RFP-LC3 fluorescence dots and decreased the decline of LC3-II after withdraw of rapamycin, indicating DRAM1 promotes autophagy flux. DRAM1 siRNA inhibited lysosomal V-ATPase and acidification of lysosomes. As a result, DRAM1 siRNA reduced activation of lysosomal cathepsin D. Similar to DRAM1 siRNA, lysosomal inhibitors E64d and chloroquine also inhibited clearance of autophagosomes and activation of lysosomal cathapsin D after 3-NP treatment. These data suggest that DRAM1 plays important roles in autophagy activation induced by mitochondria dysfunction. DRAM1 affects autophagy through argument of lysosomal acidification, fusion of lysosomes with autophagosomes and clearance of autophagosomes. DRAM1 promotes autophagy flux by enhancing lysosomal acidification.+/+) and H1299 (TP53−/−) and Hela cell lines were purchased from Shanghai Institute of Biochemistry and Cell Biology in China, and were grown at 37°C in 5% CO2 in RPMI supplemented with 2 mmol/L L-glutamine and 10% FCS. Primary mouse embryonic fibroblasts (MEFs) were derived from p53 wt and p53 KO sibling embryos, and maintained with DMEM supplemented with 10% FCS and antibiotics. 3-NP (N5636), 3-MA (M9281), carbonyl cyanide m-chlorophenylhydrazone , ATP (A6559), chloroquine (C6628), E-64d (E8640) and Z-Vad-FMK (V116) were all purchased from Sigma-Aldrich . LysoTracker Red (L7528) and LysoSentor (L7533) were purchased from Invitrogen-Molecular Probes . All cell culture reagents were purchased from Gibco  unless otherwise noted.A549 . The presence of several intense fluorescent dots in cells is indicative of the accumulation of autophagosomes. Transfection of cells with expression plasmids was performed using Lipofectamine 2000 . For each condition, the number of GFP-LC3 dots per cell was determined with a fluorescence microscopy for at least 100 GFP-LC3-positive cells.CCCAAGCTTATGCTGTGCTTCCTGAGGGGAATG (forward) and CCGCTCGAGTCAAATATCACCATTGATTTCTGTG (reverse), and subsequently digested with BamH I and Xho I and cloned in to the BamH I and Xho I sites of pcDNA4/HisA . pEGFP-N1-DRAM1 was generated through PCR primer: ATAGAATTCATGCTGTGCTTCCTGAGGGGA (forward) and CCGGGATCCTAATATCACCATTGATTTCTGTG(reverse), and products were T-A cloned in pMDTM19-T Vectors  and digested with EcoR I and BamH I and cloned into pEGFP-N1 . Transfection of cells with expression plasmids was performed using Lipofectamine 2000 .PcDNA4-DRAM1-His was generated by PCR from the I.M.A.G.E. clone for DRAM1 (Clone ID: NM_018370) with: CCACGATGTATACAAGATA and (2) CCACAGAAATCAATGGTGA. Negative siRNA TAAGGCTATGAAGAGATAC, were synthesized by GenePharma . The siRNA oligos used to target DRAM1 genes were previously validated and described in the following articles Small interfering RNAs (siRNA) targeting the following mRNA: TP53, AAGACUCCAGUGGUAAUCUAC; DRAM1, (1) For immunofluorescence microscopic examination, cells were plated on 12-mm Poly-L-Lysine-coated cover slips and cultured for 24 h, then cells were treated with siRNA and drugs. Cells were washed in PBS, fixed with 4% paraformaldehyde in PBS at 4°C for 10 min, and then washed again with PBS. The cells were permeabilized with 0.25% Triton X-100, and were then blocked with 10% normal goat serum (NGS) for 15 min. Primary antibodies: a rabbit polyclonal antibody against LC-3 , a goat polyclonal antibody against cathepsin D  and a rabbit polyclonal antibody against LAMP2  diluted in PBS were added to the cells and left for overnight at 4°C. The cover slips were washed three times before incubation with secondary antibodies using the same procedure as for the primary antibodies. The cover slips were mounted on slides with mounting medium  and were examined with a laser scanning confocal microscopy .The pattern of distribution of exogenously expressed GFP-LC3 in A549 cells was observed with fluorescent microscopy. GFP-LC3 dot formation was quantified by counting 500 GFP-LC3-positive cells and expressed as the ratio of the number of cells with at least 5 GFP-LC3 dots and the number of GFP-LC3-positive cells. The assays were independently performed by two investigators in a blinded manner and similar results were obtained.Western blot analysis was performed as scribed previously 2. Lysosomes were loaded overnight with 70000 MW FITC-dextran . and 0.5 mg/mL dextran-coupled Oregon Green 488  in DMEM supplemented with 10% FBS, chased for 2 h at 37°C with 5% CO2 in DMEM (10% FBS) to allow complete transfer of dextrans to lysosomes, and washed to remove residual dextran. Non-attached cells were removed by rinsing with PBS and the cover slips were immediately placed in a cuvette filled with growth medium or PBS and pH was estimated from excitation ratio measurements as described previously For lysosomal pH estimation, A549 and Hela cells were seeded on circular glass cover slips and grown to conﬂuence in Dulbecco’s modified Eagle’s medium (DMEM) with 10% fetal bovine serum  at 37°C, 5% CO8 cells in 2 ml) in homogenization buffer  and homogenized in a tight-fitting glass Dounce homogenizer. The homogenate was centrifuged  to remove unbroken cells and the nuclei. The supernatant was centrifuged  to remove the large organelle such as mitochondrial. The supernatant was centrifuged  to obtain the light organelle including lysosomes. The precipitation layered over 10 ml of a 27% Percoll  solution in homogenization buffer, underlayered with 0.5 ml of a 2.5 M sucrose solution. Centrifugation was done in a SW41Ti rotor  for 1.5 h at 35000 g. The layer of crude lysosomes of about 1.5 ml was collected at the bottom and then was centrifuged  to remove the other light organelle including mitochondrial at the bottom of the tube. Lysosomal fractions were equilibrated for up to 1 h in 125 mM KCl, 1 mM EDTA, and 20 mM Hepes (pH 7.5). Fluorescence was recorded continuously with excitation at 490 nm and emission at 520 nm. Upon addition of ATP , a progressive decrease in fluorescence intensity was observed, indicative of intralysosomal acidification + salt, pH 7.5, 5 mM), bafilomycin A1 (1 µM).FITC-dextran loaded A549 and Hela cells were prepared as described above. After washing in PBS, cells were resuspended  followed by Dunnett t-test or multiple means comparisons by Tukey’s test. Differences were considered significant when p<0.05.The present study examined if autophagic and apoptotic pathways are activated in A549 cells after 3-NP treatment. The results showed that 3-NP-induced a significant increase in the protein levels of DRAM1 from 3 to 72 h, with a peak induction at 24 h after 3-NP treatment . The speIt was reported that DRAM1 is a TP53 target gene. We determined the TP53 dependency in 3-NP-induced DRAM1 expression. In H1299 cells which lack of TP53, 3-NP only slightly induced DRAM1 expression, while in A549 cells which express wt TP53, 3-NP robustly induced the expression of DRAM1 . The simA). In addition, 3-NP-induced reduction of SQSTM1 was blocked by DRAM1 siRNA in A549 cells  and chloroquine (20 µM) were used to evaluate if inhibition of lysosomal functions produces effects similar to knock-down of DRAM1. Many autophagy inhibitors act on post-sequestration steps and agents, such as bafilomycin A1, that blocks autophagy activity are known to cause accumulation of autophagosomes 3-NP acts as an irreversible inhibitor of succinate dehydrogenase and thus results in an impairement of energy metabolism, oxidative stress and activation of glutamate receptors To investigate the underlying mechanism by which DRAM1 regulates autophagy, we investigated the effects of DRAM1 on autophagosome clearance. Colocalization of EGFP-DRAM1 and LysoTracker fluorescence or DRAM1 and LAMP2 immunoflurescence confirmed predominant lysosomal localization of expressed DRAM1. We first tested if DRAM1 has an effect on autophagosome turnover following induction with rapamycin. Rapamycin can stimulate the formation of autophagosome through inhibiting mTOR. Upon removal of rapamycin, autophagosomes should be cleared if autophagy pathway is normal. The present study demonstrated that rapamycin increased the abundance of autophagosomes and the number of autophagosomes returned towards the basal levels 6 h after withdrawal of rapamycin. Knock-down of DRAM1 reduced the rate of clearance of autophagosomes after rapamycin withdrawal. Galavotti et al reported that knock-down of DRAM1 inhibited targeting of SQSTM1 to autophagosomes and reduced its degradation The abundance of autophagosomes is balanced by the formation and clearance of autophagosomes. After the formation, the turn-over of autophagosomes is largely determined by the process of fusion between autophagososmes and lysosomes and degradation of autophagy contents by lysosomal enzymes. mRFP-GFP tandem fluorescent-tagged LC3 showed both GFP and mRFP signal of LC3 before the fusion with lysosomes, and exhibited only the mRFP signal when LC3 transmit into lysosomes because of lysosomal acidic environment and degradation +ATPases or VATPases. Proton transport into intracellular organelles is primarily mediated by ATPdependent proton pumps. These pumps are therefore central to pH homeostasis in organelles. Autophagosomes and their contents are cleared upon fusing with late endosomes or lysosomes containing cathepsins, other acid hydrolases, and vacuolar [H+] ATPase(v-ATPase) Lysosomes are rich in hydrolytic enzymes and are responsible for the degradation of intracellular materials captured by autophagy Lysosomes play important roles in autophagy. To test if the effects of DRAM1 on lysosomal functions are responsible for DRAM1-mediated autophagy activation after 3-NP treatment, the present study assessed the effects of lysosomal inhibitors on autophagosome accumulation in the presence of 3-NP. The results showed that elevating lysosomal pH and inhibiting lysosomal enzymes both increased accumulation of autophagosomes and inhibited cathepsin D activation. These results largely replicated the effects of knock-down of DRAM1 and suggested that DRAM1 probably regulated autophagy flux through lysosomes.It should be pointed out that DRAM1 appears regulate autophagy in both early and later stages of autophagy. DRAM1 can increase the formation of autophagosomes and the clearance of autophagosomes. These effects may work through the same mechanism as DRAM1 is a lysosomal protein and may regulates dynamics of lysosomal membranes to increase V-ATPase activity and to facilitate membrane recycle for autophagosomal formation.In conclusion, current data indicate that DRAM1 regulates autophagosome clearance through promoting lysosomal acidification and activation of lysosomal enzymes. The fusion of autophagosomes with lysosomes is an important step for autophagic degradation. In order to fully understand the role of DRAM1 in autophagy flux, the effects of DRAM1 on the fusion process between autophagosomes and lysosomes needs to be studied in the future.Figure S1DRAM1 mediated autophagy activation and lysosomal acidification in Hela cells. (A) Hela cells were transfected with DRAM1 siRNA or a non-silencing siRNA. Left: Forty-eight h after transfection of cells with DRAM1 siRNA, cells were harvested and protein levels of DRAM1 and LC3 were analyzed with immunoblotting. Right: Twenty-four hours after transfection of cells with DRAM1 siRNA, cells were treated with 3-NP (500 µM). Cells were harvested and protein levels of DRAM1 and LC3 were analyzed with immunoblotting 24 h after 3-NP. Densities of protein bands were analyzed with Sigma Scan Pro 5 and normalized to the loading control (β-actin). The data are expressed as percentage of control (non-silencing siRNA group). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA group). ##P<0.01 (3-NP treated group vs. control group). $$P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA group with 3-NP treatment). (B) Representative images of GFP-LC3 fluorescence in Hela cells transfected with GFP-LC3 and treated with DRAM1 siRNAs in the presence or absence of 3-NP (500 µM). Number of cells with GFP-LC3 dots was scored in 100 GFP-LC3-positive cells. N: the nucleus. Thin arrows: GFP-LC3 dots. The scale bar represents 10 µm Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (siRNA group vs. non-silencing siRNA group). (C) Lysosomal pH was measured ratio-metrically using fluorescent dextrans in Hela cells. WT Hela cells and DRAM1 siRNA1-treated cells were loaded with the pH-sensitive fluorescent dextrans by endocytosis for 1 h at 37°C and then subjected to pulse-chase assay in the presence or absence of the 3-NP (500 µM). Lanes 2 and 4 depict pH values obtained with FITC-dextran after the addition of 500 nM 3-NP. The data are expressed as percentage of control (non-silencing siRNA cells). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA group). ##P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA group with 3-NP treatment). (D) Lysosomal V-ATPase activity was inhibited in DRAM1 siRNA1-treated Hela cells. Lysosomes from control cells and DRAM1 siRNA1-treated cells were loaded with FITC-dextran . Hela cells were then homogenized and used for in vitro-acidification assays. Fluorescence was recorded continuously with excitation at 490 nm and emission at 520 nm. Upon addition of ATP, a progressive decrease in fluorescence intensity was observed, indicative of intralysosomal acidification. The decrement was reversed by bafilomycin A1, a V-ATPase inhibitor.(TIF)Click here for additional data file.Figure S2Activity of DRAM1 antibody was blocked by DRAM1 peptide. (A) Cells were harvested and immunoblot analysis of DRAM1 protein levels in A549 and Hela cells. Left: No peptide incubated with DRAM1 antibody before primary antibody incubation. Right: DRAM1 peptide was incubated with DRAM1 antibody for 30 min at 37°C before primary antibody incubation. (B) Cells were processed for immunofluorescence using DRAM1 antibodies (green) and DAPI  in A549 and Hela cells, and was assessed with a confocal microscopy. Left: No peptide incubated with DRAM1 antibody before primary antibody incubation. Right: DRAM1 peptide was incubated with DRAM1 antibody for 30 min at 37°C before primary antibody incubation. N: the nucleus. Thin arrows: anti-DRAM1 fluorescence.(TIF)Click here for additional data file.


Although the accessibility of HIV treatment in developing nations has increased dramatically over the past decade, viral load testing to monitor the response of patients receiving therapy is often unavailable. Existing viral load technologies are often too expensive or resource-intensive for poor settings, and there is no appropriate HIV viral load test currently available at the point-of-care in low resource settings. Here, we present a lateral flow assay that employs gold nanoparticle probes and gold enhancement solution to detect amplified HIV RNA quantitatively. Preliminary results show that, when coupled with nucleic acid sequence based amplification (NASBA), this assay can detect concentrations of HIV RNA that match the clinically relevant range of viral loads found in HIV patients. The lateral flow test is inexpensive, simple and rapid to perform, and requires few resources. Our results suggest that the lateral flow assay may be integrated with amplification and sample preparation technologies to serve as an HIV viral load test for low-resource settings. Over two-thirds of the 33.3 million people estimated to be infected with HIV worldwide live in the developing world Rapid antibody tests are widely available in developing nations, but they cannot be used to monitor HIV progression or treatment efficacy. The standard of care to monitor ART is quantitative viral load testing based on plasma HIV RNA concentration A number of commercially available viral load tests have been developed for use at the point-of-care but suffer from drawbacks that limit their widespread implementation Recently, paper-based devices have shown promise as point-of-care diagnostics because paper is inexpensive, portable, disposable by burning, and has the ability to wick fluids by capillarity Here we present a quantitative lateral flow test for detecting amplified HIV RNA that is appropriate for low-resource settings. Gold nanoparticles conjugated to complementary oligonucleotides are used as probes, and gold enhancement is implemented to improve the LOD. Our results indicate that this lateral flow assay may be used in conjunction with amplification to detect HIV RNA concentrations at clinically meaningful levels.The LFA was designed to quantitatively detect amplified HIV-1 RNA . When RNgag gene. To develop and optimize the LFA, we used a 179 bp synthetic RNA sequence containing the NASBA product sequence (in vitro transcription using the MEGAscript T7 kit (Applied Biosystems) and a plasmid containing the T7 promoter upstream of the template sequence . The in vitro transcription reaction products were purified using an RNeasy column  and quantified by measuring absorbance at 260 nm.Because the concentration of HIV found in patient plasma samples can be as low as a few copies per milliliter, nucleic acid amplification of genomic HIV RNA must be performed prior to detection with the LFA. The LFA was designed to detect a 142 bp NASBA product amplified from the HIV sequence . The synFor all experiments, the performance of the LFA was assessed quantitatively using image analysis. All LFA strips were scanned (Epson Perfection V500 Photo) and imaged using a stereo microscope (Olympus SZ61) equipped with a color camera . Images obtained with the stereo microscope were analyzed using a custom Matlab script. The green channel image was cropped to rectangular field-of-view including the captured GNPs and surrounding strip area. An intensity threshold was set by the user to make a mask, which segmented the GNP spot from the background. For images with a high noise level, the mask was drawn manually using the function ‘roispline’ (Mathworks). The intensity of each pixel was subtracted from 255 in order to invert the image data, and the signal-to-background ratio (SBR) was calculated. LFA results are expressed using the SBR.The LFA was developed to achieve the best LOD and dynamic range possible while remaining appropriate for low resource settings. We aimed to design a test that costs less than $1, requires an assay time of less than 30 minutes, detects RNA in a volume of less than 50 µL, requires minimal instrumentation, and remains stable for months at ambient temperature. The conditions that were optimized included capture oligonucleotide sequence and concentration, buffer composition, nitrocellulose flow rate, strip width, and gold nanoparticle size . To maxiin vitro transcribed target RNA for each condition to be optimized. The SBR of the detection zone was calculated for each LFA. The SBR was normalized to a maximum value of 100 for each RNA target concentration. Average normalized SBRs for each condition were used to compare conditions. The optimum conditions were defined as those that maximized the SBR, affording the best LOD and largest dynamic range.For the optimization experiments, the LFA was performed using a dilution series of For all subsequent experiments, LFA strips were fabricated using the optimized parameters. Gold nanoparticles were chosen as probes because of their large optical cross-section and stability LFA strips were assembled using glass fiber conjugate pads, nitrocellulose cards, and cellulose absorbent pads. Conjugate pads were cut into 1 cm by 0.5 cm rectangles from glass fiber sheets  using a 60-watt laser cutter  with 3% power and 5% speed. Ten microliters of GNPs were dispensed onto each pad and dried at room temperature before strip assembly. Absorbent pads  and nitrocellulose strips with a plastic backing  were cut using a guillotine cutter . Nitrocellulose strips were 3 mm wide, and absorbent pads were cut into 1 cm×0.75 cm rectangles.2 to crosslink the oligonucleotides to the nitrocellulose. Conjugate and absorbent pads were placed on the adhesive at opposite ends of the nitrocellulose strip, overlapping the nitrocellulose by approximately 2 mm. Strips were used immediately or stored in foil pouches  with desiccant .Two oligonucleotide sequences were dispensed onto the nitrocellulose strip . The target capture sequence, which is complementary to a region of the target RNA sequence, was dispensed in the center of the strip; the positive control sequence, which is complementary to the probe sequence conjugated to the GNPs, was dispensed near the end of the strip . After tin vitro transcribed target RNA were used to assess LFA performance. The RNA was prepared in 20 µL of running buffer (4x SSC with 5% formamide) and dispensed onto the conjugate pad of the lateral flow strip. After a 10 minute incubation on a heat block at 37°C, 30 µL of wash buffer (1x SSC) was dispensed onto the conjugate pad and incubated an additional 10 minutes at 37°C. During incubation, gold enhancement solution was prepared by mixing equal volumes of initiator, buffer, activator, and enhancer solutions . For experiments using silver enhancement, equal volumes of blotting initiator and blotting enhancer were mixed . Enhancement was performed by adding 30 µL of enhancement solution to the conjugate pad of the strip. LFA strips were left at room temperature to dry. LFA strips were imaged using a flatbed scanner and a stereo microscope and analyzed using the Matlab script as described previously. Dose response curves were constructed to characterize the LFA based on the average signal-to-background ratio calculated for each concentration.After the LFA was optimized, the assay was evaluated for use as a quantitative detection platform. The consistency of LFA performance was tested on two different days. On the first day, one batch of LFA strips was fabricated and the assay was performed in duplicate; on the second day, a second batch of LFA strips was made and the assay was performed in triplicate. Serial dilutions of the Because the LFA must perform consistently over time in order to be used as a point-of-care test, the stability of the assay was assessed after storing the strips and necessary reagents. At the beginning of the stability study, all lateral flow strips were fabricated on the same day and placed in foil pouches with desiccant. Half of the strips were incubated in an oven at 37°C; half of the strips were kept at room temperature. All buffers and reagents, including gold enhancement reagents, were prepared and set at room temperature for the duration of the study. The lateral flow assay was performed and analyzed on the day of strip creation and 1, 3, 7, 14, 21, and 28 days after strip creation. The two sets of strips tested on the day of fabrication were also used to assess LFA consistency (described in the previous paragraph). Dose response curves for each time point were constructed to assess the performance of the LFA over time.gag sequence (pNL43) served as the template for in vitro transcription to generate synthetic copies of HIV gag RNA . Zero, 5, 50, 500, and 5000 copies of gag RNA served as samples for NASBA reactions.To demonstrate that the LFA may serve as a detection platform in an HIV-1 viral load assay, NASBA was performed to generate reaction products for detection on LFA strips. A plasmid containing the HIV An additional control of nonspecific, genomic nucleic acid was included in some experiments to demonstrate the specificity of our assay. For this control, total nucleic acid was purified from cultured lymphoblasts  using the QIAamp DNA Blood Mini kit (Qiagen). A total of 740 ng of purified nucleic acid served as a sample for NASBA. To further ensure specificity, we designed the LFA target capture and probe sequences to bind to the amplified sequence between the regions targeted by the NASBA primer sequences. Therefore, any sequence amplified as a result of mispriming should not be detected by the LFA.In four experiments, NASBA products were generated and detected using the LFA. NASBA was performed using the NucliSens EasyQ Basic Kit as described by the manufacturer (bioMérieux). The KCl concentration in each reaction was 36 mM. Primers NASBAp5 and NASBAp6 as well as the NASBA product sequence are shown in The LFA was developed and optimized to provide quantitative detection of RNA for eventual use as part of an HIV-1 viral load test. The assay parameters shown in 10 RNA copies. The linear region of the dynamic range extended 1.5 orders of magnitude, from 11 to 12.5 log10 RNA copies. The LOD, which we define as the first concentration for which the SBR is significantly different from the negative control SBR (p<0.05), was 10.5 log10 RNA copies. For Batch 2, the dynamic range extended 3.5 orders of magnitude, from 9.5 to 13 log10 RNA copies. The linear region of the dynamic range extended 2.5 orders of magnitude, from 10.5 to 13 log10 RNA copies. The LOD was 9.5 log10 RNA copies (p<0.05).The performance of the LFA demonstrates that the assay can serve as a quantitative detection platform. The linear range was slightly larger and the LOD was lower for Batch 2 than Batch 1. This difference in performance could be explained by batch-to-batch differences in the preparation of LFA strips, as we have observed some variability in the efficiency of the oligo loading on GNPs (data not shown). Importantly, we did not observe this variability between strips of the same batch. Therefore, a standard curve may be constructed to calibrate the LFA and to account for batch-to-batch performance variability.10 RNA copies, and the linear dynamic range extended from 10.5 to 13 log10 RNA copies. Average SBRs for each pair of adjacent concentrations were compared using t-tests, which yielded p-values less than 0.05 for all but one pair (p = 0.07 for 12.5 and 13 log10 RNA copies for strips stored at 37°C). Thus, the resolution of the assay regardless of storage conditions was 0.5 log10 RNA copies. These results demonstrate that the assay performs consistently even after short-term storage, suggesting that the LFA may be used in settings where the storage conditions of test strips may vary greatly.After storing a single batch of LFA strips for various periods of time at room temperature and 37°C, the performance of the assay remained consistent . The dos10 copies/mL, while the LFA has an LOD of 9.5 log10 RNA copies in 20 µL . Therefore, NASBA was chosen to amplify HIV-1 RNA because NASBA is a well-established isothermal method that provides 10 to 12 orders of magnitude of amplification NASBA products were detected using the LFA to demonstrate that the LFA can detect amplified target RNA. The upper limit of the clinical range for HIV-1 viral load is about 6 loggag RNA were detected by lateral flow strips after dilution by a factor of 10, 100, and 1000 in running buffer. A dilution factor of 100 was sufficient for the SBR to fall within the linear range of the LFA. gag RNA (R2 = 0.93). The R2 values for all four experiments range from 0.90–0.98 with a mean value of 0.94, indicating that the LFA detects amplified RNA quantitatively . The LFA is suitable for low-resource settings and has the potential to be performed at the POC.The lateral flow assay presented here achieves a resolution of 0.5 logThe LFA represents a different approach from other assays that may potentially serve as viral load tests. While other researchers have developed quantitative tests for p24 antigen to avoid the complications of nucleic acid tests Although the LFA performs well for detecting amplified HIV RNA, some of the required conditions may be difficult to achieve at the point-of-care. Currently, the LFA requires a heat block, which may be unavailable in low-resource settings because of cost and the requirement for electricity. To overcome these obstacles, the LFA may be used in conjunction with an inexpensive battery-powered heater or exothermal chemical heating unit based on engineered phase change materials We have described a quantitative LFA that detects amplified HIV RNA by using gold nanoparticle probes and gold enhancement. The assay has the potential to serve as part of a point-of-care test in low-resource settings. Because this assay serves as a detection platform, the LFA that may be adapted to quantify RNA targets for other diseases as well. The LFA may be integrated with amplification and sample preparation to comprise an HIV viral load test for low-resource settings. Point-of-care tests for viral load measurement in low resource settings have the potential to allow proper monitoring of HIV patients receiving ART, improving the management of HIV in the developing world.Figure S1Detection of NASBA products in three additional experiments (A–C). To the left, scanned images of LFA strips are shown at the appropriate dilution for the SBRs to fall within the linear range of the assay. The total number of gag RNA copies added to each NASBA reaction are shown next to each image. Note that although the contrast was adjusted for scanned images, raw images were used for signal-to-background calculations. To the right, the SBRs for the LFA strips are shown. ‘NTC’ = ‘no target control.’ An asterisk (*) denotes that 740 ng of total nucleic acid purified from lymphoblasts was added to the sample.(TIF)Click here for additional data file.


Cold-water coral reef ecosystems are recognized as biodiversity hotspots in the deep sea, but insights into their associated bacterial communities are still limited. Deciphering principle patterns of bacterial community variation over multiple spatial scales may however prove critical for a better understanding of factors contributing to cold-water coral reef stability and functioning.Lophelia pertusa and Madrepora oculata, but not between L. pertusa color types. Within the reef center, no community distinction corresponded to geomorphologic reef zoning for both coral-generated and ambient microbial habitats. Beyond the reef center, however, bacterial communities varied considerably from local to regional scales, with marked shifts toward the reef periphery as well as between different in- and offshore reef sites, suggesting significant biogeographic imprinting but weak microbe-host specificity.Bacterial community structure, as determined by Automated Ribosomal Intergenic Spacer Analysis (ARISA), was investigated with respect to (i) microbial habitat type and (ii) coral species and color, as well as the three spatial components (iii) geomorphologic reef zoning, (iv) reef boundary, and (v) reef location. Communities revealed fundamental differences between coral-generated  and ambient microbial habitats . This habitat specificity appeared pivotal for determining bacterial community shifts over all other study levels investigated. Coral-derived surfaces showed species-specific patterns, differing significantly between This study presents the first multi-scale survey of bacterial diversity in cold-water coral reefs, spanning a total of five observational levels including three spatial scales. It demonstrates that bacterial communities in cold-water coral reefs are structured by multiple factors acting at different spatial scales, which has fundamental implications for the monitoring of microbial diversity and function in those ecosystems. Lophelia pertusa  and Madrepora oculata . By forming enormous dendritic skeletal frameworks, these corals provide complex three-dimensional living space for a plethora of mobile and sessile organisms Cold-water coral (CWC) reef ecosystems are increasingly portrayed as biodiversity hotspots on continental margins, seamounts and mid-ocean ridges around the world Often, structural complexity in CWC reefs is promoted by pronounced ecosystem heterogeneity. Unlike warm-water coral ecosystems that constitute relatively contiguous reef environments with clear wave and sun energy-related zoning Despite mounting evidence of warm-water coral reefs as structured landscapes of complex microbial communities So far, studies of CWC reef microbiology mainly focused on the identification of bacteria associated with scleractinians L. pertusa, several bacterial sequences were shared across geographically separate regions, such as the Gulf of Mexico and the Trondheimsfjord in Norway L.pertusa-associated bacteria was so far not evidenced due to significant community variations between (i) sampling locations within the same geographic area or reef complex On L. pertusa, M. oculata) and color phenotype , (iii) geomorphologic reef zoning , (iv) reef boundary , and (v) reef site  and proximity to shore .The aim of the present study was to identify patterns of bacterial communities in CWC reefs  using a L. pertusa and M. oculata, as well as from associated seawater and surface sediments, was collected from four CWC reef ecosystems on the Norwegian continental margin  or to coral color .From a pool of 440 different operational taxonomic units (OTUs) occurring in the whole data set (104 samples), between 9–223 OTUs were obtained per sample. OTU number was strongly related to microbial habitat type , and to the reef site . In addition, bacterial community structure associated with each of the four reef systems clearly differed from each other, especially between offshore  and inshore  sites  sites . These rn) sites , Fig. S4At Røst, significant intra-reef differences were detected between the up-slope reef center (Røst-in) and the down-slope reef periphery (Røst-out) . SimilarL. pertusa and M. oculata harbored significantly different bacterial assemblages  revealed surprisingly similar patterns, despite the pronounced geomorphologic reef zoning . This waversus mucus may be attributed to the circumstance that branch surface samples also included traces of coenosarc tissue, which may not only contain internal bacterial cells sensuThe observed local similarity of bacterial community structure across reef-internal zones was not maintained beyond the reef center (Røst-in), due to significant community changes towards the reef periphery , potentially indicating specialized bacterial associates. By contrast, such property was not identified for any of the mucus-contained OTUs, suggesting variable colonization of the mucus matrix by locally occurring communities. Most of the coral-associated OTUs were also found in the proximal sediments, suggesting a potential source for coral-associated bacteria. This was corroborated by the change of coral-associated bacterial communities from local  to regional (large-) scale, resulting in biogeographic patterns comparable to those of ambient bacterial communities. Host specificity of bacterial types and communities should therefore be further investigated by colonization experiments with artificial surfaces.Noticeably, the finding of low numbers of shared bacterial types combined with significant community differences related to host taxonomy, are often interpreted as signs of host specificity, implying the selection of few beneficial associates as part of commensalistic or mutualistic relationships  Microbial habitat type and (ii) coral species and color, as well as the spatial components (iii) geomorphologic reef zoning, (iv) reef boundary, and (v) reef location. Our findings revealed fundamental differences in bacterial specificity and community structure between distinct coral-generated  and ambient microbial habitats , which appeared pivotal for determining bacterial variation over all observational levels investigated. Especially the high community variability associated with coral-derived surfaces represented a consistent feature of all four CWC reef sites under study. In addition, bacterial communities changed markedly from local  to regional (large-) scale, suggesting significant biogeographic imprinting of seawater-, sediment- and even coral-associated communities, but weak microbe-host specificity. Overall, the relative effects of the different test parameters did not reflect any linear or even hierarchical relationship of bacterial community organization, but the deterministic effect of microbial habitat type and the strong effect of reef location seemed to play dominant roles in structuring bacteria in CWC reefs. The bacterial communities were structured across different spatial scales, from local within-reef habitats to regional across-reef systems, which may reflect the combined effects of local community history  and environmental filtering. As exploring bacterial diversity in CWC reefs is but one of the first steps to a better understanding of coral-microbe relationships in complex deep-sea environments, further studies need to address how changes in bacterial  diversity affect the dynamics and functioning of CWC reef ecosystems – especially in the context of global environmental changes and the protection of CWC reefs as biodiversity hotspots.This study presents the first multi-scale survey of bacterial communities associated with The four Norwegian CWC reef ecosystems sampled  compriseL. pertusa, M. oculata; L. pertusa). Geomorphologic reef zoning, as prevailing at Røst, determined the third level (ZONE), including the terrace-covered ridge crest, the rubble- and sponge-dominated ridge slope, and the clay-bearing, sparsely populated inter-ridge depression in the reef center. At the fourth level (IN-OUT), the up-slope reef center (Røst-in) was compared with the down-slope reef periphery (Røst-out) in distances of 1 m, 10 m and 100 m away from the reef margin. The fifth level (REEF) allowed a comparison of the offshore Røst site with the nearby Trænadjupet site and the two inshore sites, Tisler and Langenuen. Arranged in a nested layout, each of these study levels was considered as integral part of the respective next higher level, along an increasing gradient of complexity ranging from level one (HABITAT) to level five (REEF).Sampling was performed hierarchically, encompassing five levels of observation, including three spatial scales . The firL. pertusa, M. oculata), seawater and surface sediments was performed during two manned submersible dives down-slope across the reef  for sub-sampling of coral-associated microbial habitats. Fragments needed for branch surface and mucus sampling were maintained in flow-through tanks with in-situ water at a temperature of 10–11°C for ≤30 min until subsequent processing. Seawater was sampled with 2l-Niskin bottles attached to the submersible , or mounted on a conductivity-temperature-depth rosette sampler (Langenuen) or video-assisted steel cable  or video-assisted remotely operated vehicle . Freshly produced coral mucus was sampled by gently rinsing living coral fragments with sterile-filtered seawater and inducing mucus exudation through 2–5 min air exposure. After discarding exudate released during the first minute, subsequent production of up to 0.5 ml per fragment was collected directly from polyp surfaces by using sterile syringes. Resulting mucus-seawater mixture was concentrated onto sterile polycarbonate filters (Whatman), and frozen at −20°C until DNA extraction.After gentle rinsing with sterile-filtered  local seawater, branch surfaces of living corals were sampled by scraping an area of up to 5 cm2 surface per fragment) and sediment samples (3×1 g per scoop) were directly transferred into extraction tubes, mucus samples (up to 0.5 ml per fragment) and water samples (2–4×500 ml per Niskin bottle) on respective filter membranes. DNA yields were quantified by NanoDrop spectrophotometry . For a complete overview of sample units and replicates subjected to DNA extraction and subsequent community analyses, see Total community DNA was extracted and purified with the Ultra Clean Soil DNA Kit  following the manufacturer's instructions for maximum yield, with slight modifications. Branch samples  and corrected for multiple tests according to the Bonferroni criterion. Sources of bacterial community differences were further assessed by Permutational Multivariate Analysis of Variance Click here for additional data file.Figure S1Geographical and topographical setting of sampling events at Røst. (A) Røst bathymetry, including dive transects at Røst-in (reef center) and Røst-out , (B) Røst transversal scheme  indicating topographical reef structure, geomorphological reef zoning and single sampling stations .(TIF)Click here for additional data file.Figure S2Partitioning of bacterial OTUs between distinct coral-associated and ambient microbial habitats. Numbers indicate the amount of OTUs unique to each microbial habitat, or common to any two or all microbial habitats: (A) Bacterial OTUs associated with samples of white L. pertusa (left), red L. pertusa (middle) or M. oculata (right) and their ambient environment at Røst-in, (B) Bacterial OTUs associated with samples of all coral species/colors and their ambient environment at Røst-in (left) or at all sites combined (right).(TIF)Click here for additional data file.Figure S3Pairwise Bray-Curtis dissimilarity relationships between all community profiles. Samples are grouped according to microbial habitat type, coral species and color, geomorphologic reef zoning, reef boundary (incl. distances away from the apparent reef margin), and reef site. Cell position corresponds to the symmetrical pairing of single sample groups. Cell shading indicates the magnitude of dissimilarity between sample pairs.(TIF)Click here for additional data file.Figure S4NMDS ordinations of ARISA community profiles per microbial habitat. For each microbial habitat type, differences in bacterial community structure are plotted as related to reef site, reef boundary, geomorphologic reef zoning, coral species and color. Objects represent consensus signals for all PCR triplicates per sample and share a more similar community structure when plotting closer to each other (Bray-Curtis distance). Stress values indicate the goodness-of-fit of the 2-dimensional representation compared to the original multi-dimensional matrix.(TIF)Click here for additional data file.Table S1Overview on sampling events of living coral specimens, seawater and sediments at the different study sites. wL = white L. pertusa, rL = red L. pertusa, rM = red M. oculata. aSample lost during processing. The full station list of ARKXXII/1a is available via the PANGAEA database at: http://www.pangaea.de/ddi?retr=events/HERMES/ARK-XXII_1a.retr&conf=events/CruiseReportHTML.conf&title=StationlistofcruiseARK-XXII/1a&format=html.(DOC)Click here for additional data file.Table S2PERMANOVA of coral-associated bacterial variation done at Røst. A) Analyses considering A) reef boundary, i.e. in/out-reef location (IN-OUT) and B) geomorphologic reef zoning (ZONE) within Røst-in.aSource of variation. bAmount of explained variation. cSignificance level, assessed by 999 random permutations . dSignificance level below Bonferroni correction threshold.(DOC)Click here for additional data file.


ABC transporters represent a large family of ATP-driven transmembrane transporters involved in uni- or bidirectional transfer of a large variety of substrates. Divided in seven families, they represent 48 transporter proteins, several of which have been associated with human disease. Among the latter is ABCC6, a unidirectional exporter protein primarily expressed in liver and kidney. ABCC6 deficiency has been shown to cause the ectopic mineralization disorder pseudoxanthoma elasticum (PXE), characterized by calcification and fragmentation of elastic fibers, resulting in oculocutaneous and cardiovascular symptoms. Unique in the group of connective tissue disorders, the pathophysiological relation between the ABCC6 transporter and ectopic mineralization in PXE remains enigmatic, not in the least because of lack of knowledge on the substrate(s) of ABCC6 and its unusual expression pattern. Because many features, including structure and transport mechanism, are shared by many ABC transporters, it is worthwhile to evaluate if and to what extent the knowledge on the physiology and pathophysiology of these other transporters may provide useful clues toward understanding the (patho)physiological role of ABCC6 and how its deficiency may be dealt with. In this paper, we will summarize relevant knowledge and methods for analysis on ABC transporters which may be useful for the further study of ABCC6.ABCC6 mutations and PXE, significant progress has been made in the characterization of the ABCC6 gene and the transporter it encodes  and analyzing the vesicle content by LC/MS, several novel compounds were identified. To apply this technique for ABCC6 would imply the use of human plasma and/or hepatocytes. This transportomics technique has great potential with several advantages including a reduced number of experimental animals and would mean that identification of compounds is not a prerequisite to study their transport in vesicular transport experiments as one can fish for new substrates. Combining transportomics with untargeted metabolomics analysis would further increasethe range of potential substrates that can be identified. Disadvantages of the technique include that it is less suitable for identifying hydrophobic substrates. The complex composition of body fluids may require. fractionation to limit the effect of regulators of the transporter which could mask transport of some substrates , which can be triggered by hormones, growth factors and exogenous factors. Several examples exist of ABC transporters, such as Pgp, MRP4, BCRP, whose regulation depends on a combination of mechanisms . NuclearCFTR, MRP2 and 4, PgP and BCRP, either directly or indirectly through nuclear factors  project, which presents a novel approach to clinical and functional annotation of mutations in the as added . Though The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.