Arabidopsis miRNAs have been predicted. Putative target mRNAs have been identified for most of the candidate genes.Using bioinformatic methods, 83 novel  Arabidopsis thaliana microRNAs and their target mRNAs. This method uses characteristic features of known plant miRNAs as criteria to search for miRNAs conserved between Arabidopsis and Oryza sativa. Extensive sequence complementarity between miRNAs and their target mRNAs is used to predict miRNA-regulated Arabidopsis transcripts.A class of eukaryotic non-coding RNAs termed microRNAs (miRNAs) interact with target mRNAs by sequence complementarity to regulate their expression. The low abundance of some miRNAs and their time- and tissue-specific expression patterns make experimental miRNA identification difficult. We present here a computational method for genome-wide prediction of Arabidopsis miRNAs and identified 83 new miRNAs. Evidence for the expression of 25 predicted miRNAs came from northern blots, their presence in the Arabidopsis Small RNA Project database, and massively parallel signature sequencing (MPSS) data. Putative targets functionally conserved between Arabidopsis and O. sativa were identified for most newly identified miRNAs. Independent microarray data showed that the expression levels of some mRNA targets anti-correlated with the accumulation pattern of their corresponding regulatory miRNAs. The cleavage of three target mRNAs by miRNA binding was validated in 5' RACE experiments.Our prediction covered 63% of known Arabidopsis and O. sativa and report a wide range of transcripts as potential miRNA targets. Because MPSS data are generated from polyadenylated RNA molecules, our results suggest that at least some miRNA precursors are polyadenylated at certain stages. The broad range of putative miRNA targets indicates that miRNAs participate in the regulation of a variety of biological processes.We identified new plant miRNAs conserved between  Arabidopsis thaliana and Caenorhabditis elegans to mouse and human  are non-coding RNA molecules with important regulatory functions in eukaryotic gene expression. The majority of known mature miRNAs are about 21-23 nucleotides long and have been found in a wide range of eukaryotes, from iewed in . Experimd so far ,13,15-17C. elegans let-7 is sufficient for its specific expression at different developmental stages [While intensive research has unmasked several aspects of miRNA function, less is known about the regulation of miRNA transcription and precursor processing. A recent study shows a 116 base-pair (bp) temporal regulatory element located approximately 1,200 bases upstream of l stages . For soml stages . Expressl stages ,9,14,16.l stages ,22), eviDrosophila melanogaster, C. elegans and humans [Most known miRNAs are conserved in related species ,9,14-16.d humans ,11,23. IArabidopsis, Drosophila and humans [A known function of miRNAs is to downregulate the translation of target mRNAs through base-pairing to the target mRNA ,24,25. Id humans ,32-35.A. thaliana miRNAs and their target mRNAs. Focusing on sequences that are conserved in both A. thaliana and Oryza sativa (rice), we predicted 95 Arabidopsis miRNAs, including 12 of 19 known miRNAs and 83 new candidates. Northern blot hybridizations specific for 18 randomly selected miRNA candidates detected the expression of 12 miRNAs. The sequences of another eight predicted miRNAs were found in the public Arabidopsis Small RNA Project (ASRP) database [Arabidopsis miRNAs and 16 predicted ones. For 77 of the 83 predicted miRNAs we found putative target transcripts that were functionally conserved between Arabidopsis and O. sativa, with a signal-to-noise ratio of 4.1 to 1. Finally, we find supporting evidence for miRNA regulation of some mRNA targets using available genome-wide microarray data. The authentication of three predicted miRNA targets was validated by identification of the corresponding cleaved mRNA products.In the work reported here, we defined and applied a computational method to predict database . We alsoArabidopsis miRNA sequences from random genomic sequence, and used these properties as constraints to screen intergenic regions in the A. thaliana genome sequences for candidate miRNAs.To predict new miRNAs by computational methods, we defined sequence and structure properties that differentiate known Arabidopsis miRNAs collected in Rfam [O. sativa genome. Sequences of all 19 known Arabidopsis miRNAs had a G+C content ranging from 38% to 70%. For 15 of the 19 miRNAs, the predicted secondary structure of their precursors, or at least one precursor if a miRNA has multiple genomic loci, had a hairpin-loop length ranging from 20 to 75 nucleotides. In the hairpin structures formed by miRNA precursors, all miRNAs were found in the stem region of the hairpin, and had at least 75% sequence complementarity to their counterparts. Fifteen of 19 miRNAs were conserved with at least 90% sequence identity in the O. sativa genome. Thus, constraints of G+C content between 38 and 70%, a loop length between 20 and 75 nucleotides, and a minimum of 90% sequence identity in O. sativa were used to predict Arabidopsis miRNA.Besides the well known hairpin secondary structure of miRNA precursors, the 19 unique known  in Rfam  were evaArabidopsis intergenic sequences. As most known Arabidopsis miRNAs are around 21 nucleotides long, we used a 21-nucleotide query window to search each intergenic region for potential miRNA precursors as follows: for each successive 21-nucleotide query subsequence, if a 21-nucleotide pairing subsequence with more than 75% sequence complementarity was found downstream within a given distance (hairpin-loop length), the entire sequence from the beginning of the query subsequence to the end of the complement pairing subsequence with a 20-nucleotide extension at each side was extracted and marked as a possible hairpin sequence . The minimum and maximum hairpin-loop lengths used in this prediction were 20 and 75 nucleotides. Each 21-nucleotide query subsequence and its downstream complementary subsequence were considered as 'potential 21-mer miRNA candidates' (referred to as '21-mers'). If a series of overlapping forward query sequences and their corresponding downstream pairing sequences were all identified from the same hairpin structure, each of them was initially considered as an individual 21-mer.The first step was to search for potential hairpin structures in the O. sativa genome. The secondary structures of the resulting candidates were evaluated by mfold [Arabidopsis precursor and corresponding rice ortholog precursor both had putative stem-loop structures as their lowest free energy form reported by mfold were retained. Because some non-coding RNA genes were not included in the current Arabidopsis gene annotation, orthologs of known non-coding RNA genes other than miRNAs were subsequently removed by aligning the 21-mers to non-coding RNAs collected in Rfam with BLASTN (version 2.2.6) [The second step was to parse miRNA candidates according to their nucleotide composition and sequence conservation. A filter of G+C content between 38 and 70% was applied to all 21-mers obtained from the above step, followed by a requirement for more than 90% sequence identity in the n 2.2.6) . The 21-In cases where two or more overlapping 21-mer miRNA candidates from the same precursor were collected in the final miRNA candidate set, each miRNA candidate was scored using the following formula:score = number of mismatches +  +  + 1 if the miRNA sequence does not start with U.miRNAscore from a series of overlapping 21-mers was selected as the final miRNA candidate.The term 'terminal mismatches' in the formula above refers to consecutive mismatches among the beginning and/or ending nucleotides of a mature miRNA sequence. The term 'bulge' refers to a series of mismatched nucleotides. Because the sequences of most known miRNAs start with a U, a U-start preference was used in the formula above by penalizing non-U-start sequences. The sequence with the lowest miRNAArabidopsis genome, including 12 known Arabidopsis miRNAs and 83 new candidates. The former group corresponds to 63% of known Arabidopsis miRNAs to date (12 of 19). The remaining seven known miRNAs not included in the current prediction were filtered out as a result of their lower sequence conservation in the rice genome or longer loop length in their secondary structure, as outlined in Figure Arabidopsis MPSS data used. As most MPSS data probably represent the expression of their associated miRNAs, we were able to use them to predict the miRNA coding strand. The coding strand of miRNA candidates that were contained in the ASRP database was determined according to cloned RNA sequences (see below for details). The complete list of predicted miRNAs is shown in Additional data file 1.In total, we predicted 95 miRNA candidates in the Arabidopsis miRNA candidates and their rice orthologs is available in Additional data file 2.To gain support for the expression of the predicted miRNAs, northern blot hybridizations were carried out using RNA samples from different tissues selected to cover a spectrum of potential miRNA expression patterns. Using strand-specific oligonucleotide probes, positive signals of expression were detected for 14 out of 18 miRNA candidates tested. The results for all newly identified miRNAs are shown in Figure bona fide miRNAs , we were able to conclude that miR169b was a real miRNA. Thus, 12 candidates validated by northern blot hybridization should be annotated as bona fide miRNAs.An ASRP database has recently been made publicly available . SequencArabidopsis massively parallel signature sequencing (MPSS) data. The MPSS sequencing technology identifies unique 17-nucleotide sequences present in cDNA molecules originated from polyadenylated RNA extracted from a cell sample. By inserting cDNA molecules into a cloning vector containing distinct 32-mer oligonucleotide tags, the MPSS technology ensures that each cDNA molecule is ligated to a unique tag and that more than 99% of the total cDNAs are represented after the cloning step. Tagged cDNAs are then amplified by PCR and hybridized to microbeads that have been precoated with multiple copies of unique anti-tags complementary to one type of 32-nucleotide tag. The expression level of a particular transcript is measured by counting the number of distinct microbeads that contain the same 17-nucleotide cDNA sequence. The MPSS technology does not require prior knowledge of a gene's sequence and thus can identify novel or rarely expressed genes. For a complete description, see [To further validate the predicted miRNA molecules, we took advantage of available ion, see ,41.Arabidopsis miRNAs for unique representation in public Arabidopsis MPSS datasets and in our own MPSS datasets derived from a variety of tissues and conditions  [Arabidopsis miRNAs with the MPSS data. We found 30 MPSS signature sequences that were identical to subsequences within the flanking 500-bp sequences either upstream or downstream of 14 known miRNAs . All 30 MPSS sequences were reported in both the public and private MPSS datasets. They occurred upstream, downstream or partially overlapping with known mature miRNAs. Despite the highly repetitive nature of the Arabidopsis genome, 28 of the 30 MPSS signatures mapped uniquely to only one miRNA locus, with no matches elsewhere in the genome. Two genomic loci were found for each of the two exceptional MPSS signatures MPSS78528 and MPSS28409. For MPSS78528, the associated miRNA mir162 appeared twice in the Arabidopsis genome (upstream of At5g08180 and upstream of At5g23060) and the MPSS sequence mapped exactly to those regions. For MPSS28409, its second genomic match was on the opposite strand of an intron in gene At3g04740, which was very unlikely to be a source for MPSS sequences because samples for MPSS were prepared from mRNA or other type of polyadenylated RNA molecules, in which introns should have been processed. Thus, the MPSS data accurately reflected the expression of 14 known Arabidopsis miRNAs from a total of 19, indicating that it can be used as a source of indirect experimental support for the expression of predicted miRNAs.To assess the degree to which MPSS data could be used to support predicted miRNAs, we inspected the 19 known details) -44. We cWe then assessed the presence of MPSS signature sequences for the 83 predicted miRNAs. Using the approach described above, 23 MPSS signature sequences corresponding to the flanking sequences of 16 predicted miRNAs were found . All 23 MPSS signature sequences were present in both the public and our own MPSS datasets, and mapped uniquely to the miRNA flanking sequence. The expression of nine miRNA candidates supported by MPSS data was also tested by northern blot hybridization, with eight of them producing a positive signal. Another three miRNAs with MPSS data were found in the ASRP database . These results indicate that MPSS data indeed represent the expression of predicted miRNAs.Arabidopsis miRNAs, we compared the sequences of all 83 miRNA candidates from our prediction with sequences of the 19 known Arabidopsis miRNAs. Eight predicted Arabidopsis miRNAs exhibited high sequence similarity to one or more known Arabidopsis miRNAs and could be grouped into five clusters .To explore the relationship of predicted miRNAs to known s Figure . We coulArabidopsis and O. sativa, our method was able to identify 94% of previously confirmed or predicted mRNA targets for known conserved Arabidopsis miRNAs. Applying the method to the 83 predicted Arabidopsis miRNA candidates and their O. sativa orthologs, we predicted 371 conserved mRNA targets for 77 predicted Arabidopsis miRNAs, with an average of 4.8 targets per miRNA. The signal-to-noise ratio of the miRNA targets prediction was 4.1:1 when using randomly permuted sequences with the same nucleotide composition to miRNA sequences as negative controls that went through the same target prediction process. A complete list of these predicted target mRNAs and their pairings with miRNA sequences is available in Additional data file 4.A previous study has predicted that most known plant miRNAs bind to the protein-coding region of their mRNA target with nearly perfect sequence complementarity, and degrade the target mRNA in a way similar to RNA interference (RNAi) . AnalysiOf the 371 predicted miRNA targets, 10 were potential targets of two independent miRNAs, one (At3g54460 mRNA) was a potential target of three different miRNAs (At1g60020_5_14, At3g27883_1009, At5g62160_613_rc), and the rest were targets of a single miRNA. We assessed the biological functions of all predicted miRNA targets using gene ontology (GO) . GO termA. thaliana genome. In contrast, 139 genes encoding a general transcription factor bHLH were found in the A. thaliana genome, but only three were putative miRNA targets.Consistent with previous reports , a largeArabidopsis microarray gene expression data available from The Arabidopsis Information Resource (TAIR) [t-test on the possibility of decreased expression between transcripts listed in Table p-value of 0.04, indicating that the decreased expression observed for predicted miRNA targets is significantly different from the general expression pattern of the entire microarray data.We analyzed the expression patterns of potential targets to look for indications that they were under miRNA regulation. Twelve of the 14 miRNAs confirmed by northern blot hybridization showed an increased accumulation in flower tissue compared to the other tissues tested Figure , suggeste (TAIR) , we founArabidopsis genome). Thus, we expect the expression profile of more mRNA targets to be determined as more whole-genome tissue comparison data is available.Target mRNA fragments resulting from miRNA-guided cleavage are characterized by having a 5' phosphate group, and cleavage occurs near the middle of the base-pairing interaction region with the miRNA molecule. Using a modified RNA ligase-mediated 5' rapid amplification of cDNA ends (5' RACE) protocol, we were able to detect and clone the At3g26810 mRNA fragment corresponding precisely to the predicted product of miRNA processing  were missed using our selected parameters. However, relaxing the loop length range to include all known miRNAs increased the number of candidate hairpins from around 180,000 to around 337,000 (a 53% increase). As the method requires stringent miRNA sequence conservation between Arabidopsis and O. sativa, miRNAs with little or no sequence conservation in other genomes will be overlooked by this method. Given the current knowledge of miRNAs, it is difficult to develop computational methods to distinguish non-conserved miRNAs from noise. The prediction method developed here is not specific for Arabidopsis and can be applied to other pairs of related genomes as well.The prediction method developed in this study uses computable sequence and structure properties that characterize the majority of the known We attained a 67% success rate of northern blot hybridization on all tested miRNA candidates, demonstrating the expression of 12 miRNAs from a total of 18 tested candidates. Failure to detect miRNA candidates by northern blot hybridization could be due to the limited number of sample tissues tested, as specific miRNAs may be expressed only under particular conditions  or in specific cell types. For instance, further analysis of miR169g* . The MPSS sequence locations and orientations indicate that they are not transcripts derived from surrounding annotated genes. All but one tested miRNA candidates with MPSS evidence produced positive signals in northern blot hybridizations. As MPSS cDNA libraries are generated using polyadenylated RNA molecules [Arabidopsis miRNAs from a total of 19 in these datasets strongly indicates that at least some, if not all, plant miRNAs have a polyadenylated precursor form at some stage of their biogenesis.We made an intriguing discovery by identifying known olecules ,41,43,44Predicted miRNAs detected by both northern blot hybridization and MPSS have consistent tissue-specific expression profiles under both methods. This supports the notion that the MPSS data reflect miRNA expression patterns. The public MPSS datasets are accessible only through an online interface that allows direct query of 17-nucleotide MPSS sequences. Direct comparison of the public sequences and predicted miRNAs was not possible. Thus, we were limited in our analysis to inquire whether a private MPSS sequence was also in the public MPSS dataset. Consequently, only MPSS sequences that appeared in the private set alone or in both sets were available to support miRNA prediction. The public MPSS dataset has 120-fold more signature sequences  than our private MPSS dataset . Thus, we expect far more MPSS evidence for expression of the predicted miRNAs to be found in the public MPSS datasets when the public MPSS data are available to be compared locally.O. sativa functional ortholog among the top 500 rice miRNA targets were considered as potential miRNA target genes. Because all miRNA candidates reported here are highly conserved in rice, it is expected that their mRNA targets should also be conserved. Transcripts encoding proteins with ambiguous annotations, such as those for hypothetical proteins, expressed proteins and putative proteins, are not included in the target prediction because of the difficulty in identifying their orthologs in the O. sativa genome. Thus, the absence of predicted mRNA targets for the minority of the miRNAs may be due to the unfinished annotation of the O. sativa genome or to the divergence of target mRNA sequences that may preclude its identification.We used phylogenetic conservation as a constraint on miRNA target mRNA prediction: only transcripts that had at least one Arabidopsis miRNAs in target mRNA translation repression, in this prediction we allowed gaps and mismatches in the putative Arabidopsis miRNA::mRNA pairs. The free energy of 90% of the predicted miRNA::mRNA pairs is lower than the average free energy of known animal miRNA::mRNA pairs  [Gaps and mismatches are commonly seen in known animal miRNA::mRNA base-pairing interactions and, as a result, miRNA binding represses the translation of their targets . Althougcal/mol) , indicatOur prediction of target mRNAs for the new 83 miRNA candidates reveals that a broad functional range of genes may be regulated by miRNAs (Table Arabidopsis genome (2.1%) [We took advantage of available microarray data to assess the relative expression levels of potential mRNA targets in tissues in which their miRNAs were expressed. For mRNA targets of several newly identified miRNAs, we found reduced expression levels in RNA samples from flowers compared to the whole plant. Accordingly, we identified the cleavage product of At3g26810 mRNA, and those of another two homologous genes, At1g12820 and TIR1 (At3g62980), to confirm them as targets of the same miRNA (miR393a). These genes encode F-box proteins, and TIR1 in particular is involved in auxin-mediated protein degradation . Interese (2.1%) . RemarkaArabidopsis genome version 3 and the O. sativa genome released by The Institute for Genome Research (TIGR) on 22 July 2002 [A. thaliana and the O. sativa genomes were extracted according to the annotations provided by TIGR. A scanning algorithm implemented in the Perl programming language was used to search for possible hairpin structures within each intergenic sequence in A. thaliana. The method inspects each successive 21-nucleotide query window in each intergenic region, with two nucleotide increments, and searches for downstream complementary sequences with up to 25% mismatches. We restricted the distance from the last base of the forward query sequence and the first base of the downstream complementary pairing sequence to a minimum of 10 nucleotides and a maximum of 150 nucleotides (loop length). For each 21-nucleotide query, the loop length was increased one nucleotide at a time, and all downstream 21-nucleotide pairing sequences with more than 75% identity to the complement of the query sequence were considered as possible 'pairing sequences'. For each query sequence, the downstream complementary sequence with the fewest mismatches was saved as the pair sequence for the query. Insertions and deletions were allowed in the alignment and were counted as mismatches. Sequences from the start of a qualified querying sequence to the end of its downstream complementary pairing sequence were considered as a potential miRNA precursor with putative hairpin structure. Twenty extra nucleotides were extracted from the genome at each end of a potential miRNA precursor for the purpose of structure check using mfold [The uly 2002  and 24 July 2002 , respectng mfold .O. sativa intergenic regions with 90% or higher sequence identity. The secondary structure of Arabidopsis miRNA candidate precursors and their rice precursor orthologs was evaluated using mfold [Arabidopsis precursor and rice ortholog precursor both had a hairpin-like folding as their lowest energy states were considered as miRNA candidates. A sequence alignment search against non-coding RNAs collected in Rfam [A G+C-content filter and a loop-length filter were applied to the 312,236 hairpin structures obtained. Only hairpins with a loop length between 20 and 75 nucleotides and 21-mer sequences with a G+C-content between 38 and 70% were analyzed further. The remaining 21-mer sequence pairs were aligned with rice intergenic regions using BLASTN (version 2.2.6) to identify homologous sequences in  in Rfam  using BLA. thaliana (Col-0) were used to extract total RNA using the trizol reagent (Invitrogen). Samples of 20 μg total RNA were resolved in a 15% polyacrylamide/1x TBE/8 M urea gel and blotted to a zeta-probe membrane (BioRad). DNA oligonucleotides with the exact complementary sequence to candidate miRNAs were end-labeled with [γ-32P]ATP and T4 polynucleotide kinase (New England Biolabs) to generate high specific activity probes. Hybridization was carried out using the ULTRAHyb-Oligo solution according to the manufacturer's directions (Ambion), and signals were detected by autoradiography.Two-day-old seedlings, 4-week-old adult plants, root-regenerated calluses and mixed-stage flowers of Arabidopsis miRNAs. If an intergenic region encoding a miRNA had fewer than 500 nucleotides on either side of the miRNA locus, sequences were extracted up to the neighboring gene.To obtain genomic regions corresponding to miRNA precursors, we extracted 500 nucleotides upstream and downstream of every genomic locus of all known and predicted Arabidopsis MPSS datasets were used in this study: a MPSS database from abscisic acid (ABA)-treated plants, and plants with elevated levels of endogenous cytokinin [Arabidopsis tissues at different developmental stages - around 10-week-old active growing calluses initiated from seedlings, mixed-stage buds and immature flowers, 14-day-old leaves, 14-day-old roots and 24- to 48-h post-fertilization siliques [Two ytokinin ,44 and asiliques .Arabidopsis miRNAs and their O. sativa orthologs were used as query datasets. mRNA sequences of the Arabidopsis and O. sativa annotated genes were used as target datasets. Gaps were allowed in the pairing of miRNA and their target mRNAs. Mismatches were preferred over gaps by assigning higher penalties to gaps in the alignment algorithm. Consecutive gaps were preferred over scattered individual gaps by assigning higher penalties to gap opening than to gap extension. The top 500 putative hits from Arabidopsis miRNA target list and their O. sativa ortholog target list were compared. For each mRNA hit of an Arabidopsis miRNA, if a rice ortholog from the same gene family was also found among the top 500 rice miRNA hits, the Arabidopsis mRNA hit was selected as a putative miRNA target.miRNA target gene prediction was performed by aligning miRNA sequences with target mRNA sequences using the TimeLogic implementation of the Smith-Waterman nucleotide-alignment algorithm. Sequences of known and predicted Tissue comparison (reference vs flower) microarray data used for target gene validation were downloaded from TAIR . mRNA saTo identify the products of miRNA-directed cleavage we used the First Choice RLM-RACE Kit (Ambion) in 5' RACE experiments, except that we used total RNA (2 μg) for direct ligation to the RNA adaptor without further processing of the RNA sample. Subsequent steps were according to manufacturer's directions. Oligonucleotide sequences for PCR amplification of At3g26810, At1g12820 and TIR1 (At3g62980) are available upon request.Arabidopsis miRNAs using the MEME motif-searching software and Smith-Waterman gapped local alignment to identify homologs of known miRNAs. Pairs of aligned sequences were grouped by transitive closure, and multiple alignments were generated with ClustalW [Predicted miRNAs were compared to known ClustalW -54. The We used mfold program to calculate the free energy (ΔG) of predicted miRNA::mRNA pairs. For each miRNA::mRNA pair, the miRNA sequence was linked by 'LLL' to the target mRNA sequence. The 'LLL' linker sequence tells the mfold program to treat the miRNA and target sequence as two separate RNA sequences for energy calculation .Arabidopsis miRNAs, some of which are included among the predicted miRNAs in this work, confirming the validity of our approach.During revision of this manuscript, three groups -57 reporArabidopsis miRNA candidates and their rice orthologs (Additional data file Arabidopsis miRNAs (Additional data file The following additional data are available with the online version of this paper: the complete list of predicted miRNAs (Additional data file The complete list of predicted miRNAsClick here for additional data fileArabidopsis miRNA candidates and their rice orthologsA full list of the secondary structures of predicted precursors of Click here for additional data fileArabidopsis miRNAsMPSS evidence for known and predicted Click here for additional data filea complete list of predicted target mRNAs and their pairing with miRNA sequencesClick here for additional data file


The Cold Spring Harbor Laboratory Oral History Collection presents interviews with over 80 leading scientists, drawn from the fields of molecular biology and genetics That there's going to be a great comfort with people standing up and challenging a particular perspective. That young people are welcome. That old codgers are welcome as well. This is sort of the idyllic way that science is supposed to happen. And Cold Spring Harbor [Laboratory] provides that opportunity.”—Francis Collins, Cold Spring Harbor Laboratory Oral History CollectionCold Spring Harbor Laboratory (CSHL) has played a significant role in the development of genetics, a role that began at the Laboratory in 1904, just a few years after the discovery of Mendel's work. In 1908, George Shull's development of hybrid corn (maize) shaped the future of modern agricultural genetics; 55 years ago, Barbara McClintock worked on maize cytogenetics and discovered “jumping genes”; and in 1977, Richard Roberts was a codiscoverer of “split genes.” Throughout the 1950s, the Phage Course at CSHL trained many of the leaders of the then new field of molecular genetics, and the Laboratory's courses continue to train young scientists.CSHL Archives is a unique repository of rare books, manuscripts, photos, and scientific reprints that document the institution's significant contributions to molecular genetics research over the past 100 years. In 2000, the Archives received James Watson's personal collection of original materials, including manuscripts, correspondence, photographs, lab notes, lectures, memorabilia and reprints, for processing and preservation. This is an invaluable documentary resource for the history of molecular biology. While organizing over 60 years of Watson's correspondence, we realized that many of his correspondents have passed through CSHL as researchers, participants in the laboratory's leading scientific meetings, or instructors of our courses. We decided to talk to these scientists and record their commentaries, stories, and personal memories. These oral history interviews will enhance our collection by adding the voices of participants in significant scientific events.The project began in 2000. In 2002, we received a grant from the Gladys Brook Foundation that enabled us to purchase state-of-the-art recording and editing equipment for carrying out this project, and created a web site exhibiting taped conversations. During the last three years, we have interviewed over 80 scientists from several generations working in different fields of molecular biology and genetics, and have developed a video collection at CSHL's Carnegie Library. (A customized DVD of this collection is available.)The unique environment of the CSHL facilitated our task. Throughout the year, researchers from all over the world attend our scientific meetings to exchange information and ideas about their research, so most of the interviews took place at the Laboratory during these meetings. The scientists were always very pleasant and receptive to our requests for interviews. Other interviews were conducted in Cambridge and Boston, Massachusetts; La Jolla, California; Washington, DC; and abroad, in Oxford, England, and Sydney and Melbourne, Australia.Interviewing scientists was very exciting. We often wanted to come back for an additional interview because one or two hours was not enough time to collect all the memories that they wanted to share with us. It is well known that Sydney Brenner is a superb storyteller. After spending a few hours listening to Sydney in La Jolla, California, I received a call confirming my meeting with Francis Crick, which was to take place in the next 30 minutes. Despite looking forward so much to this meeting, I was torn between my present interview, in which I was deeply involved, and my next, which I was gladly anticipating.library.cshl.edu) provides an opportunity to “meet and get to know” the leading minds of molecular biology and genetics. We hope that our site makes the history of science come to life. These interviews can be helpful to all categories of users: students, scientists, historians, writers, journalists, and others.The CSHL Oral History Collection web site (The site is searchable and allows visitors to cross-reference people and information, and links them to the world of narratives and anecdotes, as told in the voices of those interviewed. Selected interview clips are organized into five topics: CSHL, James D. Watson, prominent scientists, scientific experience, and genome research. Each topic is divided into subtopics; for example, “Genome Research” includes: involvement in genomics, mechanism of the Human Genome Project, challenges of the Human Genome Project, dangers of genomic research, the future of genomics, and others. “Woman in Science”  is one oOur Web site adds a new dimension to the papers and books written by leading scientists—now you can listen to them discuss their work in their own voices! On this site you will meet a remarkable range of scientists, from friends and students of Barbara McClintock and Jim Watson, to the evolutionist Ernst Mayr, to the genome bioinformaticist James Kent. You'll hear Nancy Hopkins, Tom Maniatis, Matt Ridley, and Joan Steitz, to name just a few.We remain committed to our objective of providing an unprecedented and exciting approach for scientists, historians, scholars, and students to gain a firsthand account of the history of molecular biology and the stories behind the people who contributed to it. We have many more interviews planned, so in the future you can expect to meet even more of the fascinating figures who illuminate the glory days of the world of molecular biology.


Sleep duration may be an important regulator of body weight and metabolism. An association between short habitual sleep time and increased body mass index (BMI) has been reported in large population samples. The potential role of metabolic hormones in this association is unknown.Study participants were 1,024 volunteers from the Wisconsin Sleep Cohort Study, a population-based longitudinal study of sleep disorders. Participants underwent nocturnal polysomnography and reported on their sleep habits through questionnaires and sleep diaries. Following polysomnography, morning, fasted blood samples were evaluated for serum leptin and ghrelin (two key opposing hormones in appetite regulation), adiponectin, insulin, glucose, and lipid profile. Relationships among these measures, BMI, and sleep duration  were examined using multiple variable regressions with control for confounding factors.p for slope = 0.01), with a predicted 15.5% lower leptin for habitual sleep of 5 h versus 8 h, and high ghrelin (p for slope = 0.008), with a predicted 14.9% higher ghrelin for nocturnal (polysomnographic) sleep of 5 h versus 8 h, independent of BMI.A U-shaped curvilinear association between sleep duration and BMI was observed. In persons sleeping less than 8 h (74.4% of the sample), increased BMI was proportional to decreased sleep. Short sleep was associated with low leptin (Participants with short sleep had reduced leptin and elevated ghrelin. These differences in leptin and ghrelin are likely to increase appetite, possibly explaining the increased BMI observed with short sleep duration. In Western societies, where chronic sleep restriction is common and food is widely available, changes in appetite regulatory hormones with sleep curtailment may contribute to obesity. The less people sleep the higher their risk for being overweight. This study shows that sleep duration affects appetite-regulating hormones In population studies, a dose-response relationship between short sleep duration and high body mass index (BMI) has been reported across all age groups –7. In thA number of hormones may mediate the interactions between short sleep duration, metabolism, and high BMI. We hypothesized that the two key opposing hormones in appetite regulation, leptin and ghrelin ,9, play The institutional review board of the University of Wisconsin Medical School approved all protocols for the study, and informed consent was obtained from all participants. The Wisconsin Sleep Cohort Study is an ongoing longitudinal study of sleep habits and disorders in the general population . BrieflyThis investigation is based on Wisconsin Sleep Cohort Study data collected from the mailed sleep surveys, overnight studies, and 6-d sleep diaries. Overnight studies were conducted in laboratory bedrooms, with participants setting their own sleep and rise times. After informed consent was obtained, questionnaires on lifestyle and health history were administered, and height and weight measured. A blood sample was collected shortly after awakening from overnight polysomnography.An 18-channel polysomnographic system was used to assess sleep states, and respiratory and cardiac variables . Sleep wPolysomnographic measures of sleep duration just prior to blood sampling were used to evaluate degree of “acute sleep restriction.” “Total sleep time” was total hours of polysomnographically defined sleep. “Wake after sleep onset” (WASO) was hours of wake time after three epochs of sleep had occurred. “Sleep efficiency” was total sleep time divided by time from lights out until arising in the morning.Two variables were used to evaluate degree of “chronic sleep restriction” by estimating average nightly sleep duration: (i) “usual sleep” (from questionnaires) and (ii) “average nightly sleep” (from sleep diaries).Usual sleep was estimated from the following questions: how many hours of sleep do you usually get in (a) a workday night? (b) a weekend or non-work night? These questions were included in all mailed surveys and were added to questionnaires completed at the overnight study in 1998. For participants studied after 1998, data from questionnaires administered at the overnight study were used (58%); for the remainder of the sample, data from the mailed survey closest in time to the overnight study were used. Usual sleep was calculated as (5 × workday sleep + 2 × weekend sleep)/7.Average sleep duration was also estimated using a 6-d sleep diary, kept by 721 participants as part of an added protocol to measure daytime sleepiness. The median time between the blood collection and completion of the diary was 18 d. Almost all diaries (97%) were completed within 6 mo of blood sampling. In diaries, participants recorded the time they went to bed and arose each day, and the duration of any naps. “Average nightly sleep” was calculated as the sum of the hours between bedtime and arising divided by six. “Average nightly sleep plus naps” added naps to the above sum.For the analysis of the association of BMI and sleep duration, the sample comprised 1,040 participants with at least one 6-d sleep diary. Of these, 4-, 8-, and 12-y follow-up studies had been completed by 397, 179, and 11 participants respectively (1,828 visits), providing repeated measures data for greater analytic efficiency and precision.I) + log (G)), where I is fasting insulin and G is fasting glucose [Following overnight fasting, serum was collected soon after awakening and stored at −70 °C. All samples were assayed in duplicate. It was not possible to assay samples from all participants in all assays because of the volume of serum available; this particularly affected the ghrelin assay, which required the most volume. Leptin and insulin were determined using enzyme-linked immunoassays . Total ghrelin and adiponectin were measured by radioimmunoassay (Linco Research). Sensitivity for the leptin and insulin enzyme-linked immunoassays was 0.5 ng/ml and 2 μU/ml, respectively. Sensitivity for the ghrelin and adiponectin radioimmunoassays was 10 pg/ml and 1 ng/ml, respectively. Intra- and inter-assay variations were all less than 5% and less than 10%, respectively. The quantitative insulin sensitivity check index (QUICKI) was 1/(log ( glucose ,16.n = 1,828) from 1,040 participants with sleep diary data available. Mixed modeling techniques were used to account for within-subject correlation for participants with multiple visits. SAS procedure mixed was used for modeling and hypothesis testing using robust standard errors and a compound symmetric within-subject correlation structure. All reported p values are two-sided. For illustrative purposes, changes in leptin, ghrelin, and BMI for different sleep amounts were calculated at the average values and sex distribution of the relevant sample.All analyses were cross-sectional and performed using SAS/STAT 8.2. Leptin, ghrelin, and adiponectin were square-root transformed and insulin log transformed based on the distribution of residuals from the multivariate regression models. We evaluated the relationship of age, sex, BMI, and time of storage of blood sample on hormones using multiple regression. Partial correlations adjusted for age, sex, and BMI were calculated for hormones and QUICKI, with and without control of other potential confounders. The relationships between hormones and sleep were evaluated using multiple linear regression after control for potential confounders including age, sex, BMI, SDB, and morningness tendencies (as measured using the Horne-Ostberg questionnaire, an indirect surrogate of earlier rising time). In all analyses involving insulin, glucose, and QUICKI (but not leptin, ghrelin, and adiponectin), participants with diabetes (self-reported diagnosis, or currently taking insulin or diabetic medications, or with glucose >300 mg/dl) were excluded. Participants with SDB were not removed from the analyses shown. When controlling for AHI in models, participants who used continuous positive airway pressure or who had inadequate sleep were excluded. Because controlling for AHI did not significantly change the sleep-hormone regression coefficients, these analyses are not shown. The relationship of BMI with average nightly sleep was evaluated using a quadratic fit. This was examined using multiple visits 2 coefficient = 0.156, p = 0.008; the two coefficients define a curve). The minimum BMI was predicted at 7.7 h of average nightly sleep. The most striking portion of the curve was for persons sleeping less than 8 h (74.4% of the sample), where increased BMI was proportional to decreased sleep. An increase in BMI from 31.3 to 32.4 (+3.6%) corresponded approximately to an average nightly sleep duration decrease from 8 h to 5 h, as estimated at the mean age (53.1 y) and sex distribution  of the sample with available sleep diary data.p = 0.01). When evaluated at the average values and sex distribution of our sample, a decrease from 8 to 5 h in average nightly sleep was associated with a predicted 15.5% decrease in leptin. p = 0.008). When evaluated at the average values and sex distribution of our sample, a decrease from 8 to 5 h of polysomnographically defined total sleep time was associated with a predicted 14.9% increase in ghrelin. There was no significant correlation between sleep duration (acute or chronic) and serum adiponectin, insulin, glucose, or QUICKI. Results of our analyses were unchanged after adjusting for the weighted sampling scheme.Using polysomnography to measure objective sleep immediately prior to blood sampling, ghrelin correlated significantly with total sleep time, sleep efficiency, and WASO . Using qWe found that habitual sleep duration below 7.7 h was associated with increased BMI, similar to findings in other studies including children ,17, adolPrevious studies have shown that both acute sleep deprivation  and chroLevels of ghrelin, a potent stimulator of appetite ,24,25, wr = 0.55, p < 0.001). One-night polysomnographically defined total sleep time had a similar intra-person mean difference (0.10 h), with a somewhat larger standard deviation (0.68) for 713 participants with at least three sleep studies.Our findings are strengthened by the large and well-characterized population-based sample, attention to bias and confounding factors, and in-laboratory polysomnographic data. The changes in hormones with sleep duration were consistent and of significant magnitude. They also represent the first demonstration of a correlation between peripheral hormone levels and both self-reported (questionnaire and diary data) and polysomnographically determined sleep amounts in a general population sample. While these data are more comprehensive than previous studies on this topic, some misclassification error may exist because of intra-person variability or limitations of polysomnographic measurement. Little is known about the stability of self-reported sleep duration and polysomnographic measures of sleep duration over time. We examined the stability of the self-reported sleep duration data, and found these measures to be stable. For 860 participants who completed three surveys, the mean (standard deviation) of intra-person differences in usual sleep for two 5-y periods was 0.10 (0.47) h. For 190 participants with at least three sleep diaries, the mean (standard deviation) of intra-person differences in average nightly sleep for two 4-y intervals was 0.09 (0.41) h. Furthermore, the subjectively reported hours of usual sleep and the diary-derived average nightly sleep values were highly correlated (r = 0.12, p < 0.001), supporting the concept that these measures reflect long-term and short-term changes in sleep amounts, respectively. Our findings are in agreement with the current view that leptin is important in signaling long-term nutritional status while ghrelin has a more significant role in acute hunger. The changes in leptin and ghrelin with sleep restriction could, therefore, provide a powerful dual stimulus to food intake that may culminate in obesity.Elevated ghrelin mainly correlated with acute sleep loss as measured by polysomnography immediately prior to blood sampling see B, while Longitudinal and intervention studies will be necessary to define further the link between sleep curtailment and increased BMI. Only total ghrelin was measured, since active octanoylated ghrelin is unstable. Although both total and active ghrelin appear to be regulated in a similar and parallel manner, future studies will need to focus on measurement of the biologically active form. Other potentially important appetite regulatory hormones, such as PYY 3–36 , were noHormone measurements were all performed on a single fasted, morning sample and may not reflect the 24-h profile. It is possible that participants with shorter sleep woke up earlier and that hormone differences may be partially related to circadian time. Leptin and ghrelin levels rise slightly during the night , and thiAnimal studies have suggested a link between sleep and metabolism ,32. In rSleep loss from a baseline of 7.7 h was associated with a dose-dependent increase in BMI. This was the predominant effect in a population increasingly curtailing sleep . Sleep gInsulin resistance with sleep deprivation has been reported in a laboratory study of young, healthy volunteers . When coOur results demonstrate an important relationship between sleep and metabolic hormones. The direct effect of chronic partial sleep loss on food intake, energy expenditure, and obesity now needs to be explored. Altering sleep duration may prove to be an important adjunct to preventing and treating obesity.Recent studies have shown that there is a link between sleeping less and gaining weight. It isn't clear why there is this link—perhaps, for example, those who are awake in the middle of the night tend to head for the refrigerator for a snack. Another possibility is that the amount of sleep that we have might affect the hormones that control our appetite. We know that extreme sleep deprivation affects the level of leptin, a hormone that controls appetite. Here, the researchers wanted to study levels of leptin and other appetite hormones under more normal conditions, in people with a range of sleeping habits.The researchers studied participants in a large sleep study that has been going on in Wisconsin for over 15 years. These participants have been filling out questionnaires about their sleep habits and their health in general, have kept sleep diaries, and have occasionally spent a night in the laboratory, where researchers studied their sleep in more detail. After sleeping overnight in the laboratory, the participants gave blood samples, which were tested for hormones.The researchers found that people who slept less were on average heavier. And people who slept less had lower levels of leptin and higher levels of ghrelin, another hormone that controls food intake.The combination of low leptin and high ghrelin is likely to increase appetite. In other words, short sleep might stimulate appetite, which increases weight.Future studies need to examine the effect of regular short sleeping hours on appetite, food intake, and obesity. These studies could help to answer the question of whether the rise in obesity in many societies is partly due to the fact that people are sleeping less. And it seems well worth testing whether increasing sleep to seven or eight hours per night could help people to lose weight.http://www.sleepfoundation.org/features/obesity.cfmNational Sleep Foundation Web page on obesity and sleep: http://www.wfsrs.org/homepage.htmlWorld Federation of Sleep Research Societies: http://www.rems.com.ar/Red en Medicina del Sueño: http://www.esrs.org/European Sleep Research Society:


In the present study we tested the hypothesis that progression of streptozotocin (STZ)-induced diabetes (14-days to 28-days) would produce renal and vascular dysfunction that correlate with altered p38- mitogen-activated protein kinase (p38-MAPK) phosphorylation in kidneys and thoracic aorta.Male Sprague Dawley rats (350–400 g) were randomized into three groups: sham (N = 6), 14-days diabetic (N = 6) and 28-days diabetic rats (N = 6). Diabetes was induced using a single tail vein injection of STZ (60 mg/kg, I.V.) on the first day. Rats were monitored for 28 days and food, water intake and plasma glucose levels were noted. At both 14-days and 28-days post diabetes blood samples were collected and kidney cortex, medulla and aorta were harvested from each rat.The diabetic rats lost body weight at both 14-days (-10%) and 28-days (-13%) more significantly as compared to sham (+10%) group. Glucose levels were significantly elevated in the diabetic rats at both 14-days and 28-days post-STZ administration. Renal dysfunction as evidenced by renal hypertrophy, increased plasma creatinine concentration and reduced renal blood flow was observed in 14-days and 28-days diabetes. Vascular dysfunction as evidenced by decreased carotid blood flow was observed in 14-days and 28-days diabetes. We observed an up-regulation of inducible nitric oxide synthase (iNOS), prepro endothelin-1 (preproET-1) and phosphorylated p38-MAPK in thoracic aorta and kidney cortex but not in kidney medulla in 28-days diabetes group.The study provides evidence that diabetes produces vascular and renal dysfunction with a profound effect on signaling mechanisms at later stage of diabetes. Diabetes is a complex and multifarious group of disorders characterized by hyperglycemia that has reached epidemic proportions in the present century. Infection is a leading cause of morbidity and mortality among the diabetic population . DiabeteMitogen-activated protein kinases (MAPKs) are implicated in the etiology of diabetes ,5. MAPKstype 1 and type 2, is associated with decreased NO bioavailability [We have earlier demonstrated that diabetes during coronary artery bypass grafting, and chronic peritoneal sepsis produced an imbalance in the myocardial and systemic ET-1 and nitric oxide (NO) profiles ,12. Howelability ,14. Conflability ,16. We hlability  and makelability . We antiWe hypothesize that progression of diabetes [mild (14-days) to moderate (28-days)] would produce renal and vascular dysfunction that correlate with altered p38-MAPK phosphorylation in kidneys and thoracic aorta. Therefore, the specific aims of the study are to characterize the progression of STZ-induced renal and vascular dysfunction at 14- and 28-days; and to examine if the progression of STZ-induced diabetes would alter the biosynthesis and activation of ET-1, NO and the phosphorylation of p38-MAPK and ERK1/2 in thoracic aorta, kidney cortex and kidney medulla.NIH Guide for the Care and Use of Experimental Animals, and were approved by the Institutional Animal Care and Use Committee of North Dakota State University.Male Sprague-Dawley rats (Harlan, Indianapolis, IN) weighing 350–400 g were used in the study. The rats were acclimatized to the laboratory conditions for at least 7 days following their arrival. All animal experiments were conducted in compliance with humane animal care standards outlined in the All animals were age-matched at the onset of the study. The rats were randomly divided into three groups: control, 14-days and 28-days diabetic rats (n = 6 for each group).®, Bayer Corporation, IN) 2 days after STZ-injection. Diabetes was confirmed if blood glucose > 200 mg/dL. The animals were not given insulin supplementation. Food intake and water intake were examined everyday after STZ-injection.Diabetes was produced by a single tail vein injection of streptozotocin  . DiabeteThe non-diabetic control rats received an injection of 1 mL/kg saline. 14-days and 28-days post-STZ administration recordings of systemic hemodynamics, carotid blood flow, and renal arterial blood were done. Arterial blood was collected in plastic tubes containing EDTA (1 mg/mL) and heparin (5 units/mL) to determine the plasma concentration of ET-1, NO by-products (NOx) and creatinine. The animals were euthanitized by pentobarbital (100 mg/kg, I.P.), the thoracic aorta and kidney were harvested. The concentration of ET-1, NOx, creatinine and protein expression of preproET-1, iNOS, eNOS, phosphorylated p38-MAPK (pp38-MAPK), total p38-MAPK, phosphorylated ERK, total ERK were determined in the thoracic aorta, kidney cortex and kidney medulla obtained from each animal.®, Abbott; 50 mg/kg).Separate group of animals (N = 6) were used for hemodynamic study. On the day of experiment, the rats were anesthetized with an intraperitoneal injection of pentobarbital sodium  was placed carefully around the artery. The probe was manually positioned so that the artery was centered within its window and then probe was held in position. Through a sterile 10 CC syringe loaded with sterile K-Y brand lubricating jelly (Johnson & Johnson, Arlington, TX), the acoustical window within the flow probe was filled while avoiding any air bubble.Under pentobarbital (50 mg/kg I.P.) anesthesia, rats were placed in dorsal recumbency and through a midline cervical incision, the left common carotid artery was identified and carefully separated from adhering connective material. The carotid artery was cleared from the vagal nerve and a Transonic® flow probe was placed around it. The probe was manually positioned so that the artery is centered within the window and the probe was held in position. The acoustical window within the flow probe was filled with K-Y brand lubricating jelly (Johnson & Johnson, Arlington, TX). Renal and carotid artery blood flow was measured using Transonic® flow meter T206 attached to MP100 system of Biopac Systems Inc., CA via analog to digital conversion. The MP100 system was calibrated with minimum and maximum flow capacity of the individual probe connected to the flow meter. The sampling of data was carried out at 1000 Hz and recorded to a dedicated computer using AcqKnowledge™ software.Under pentobarbital anesthesia, rats were place in dorsal recumbency, and through a midline abdominal skin incision the left renal artery was carefully separated from renal vein and a 0.5 VB Transonic-1.Kg-1) normalized to individual rat body weight was calculated.The concentration of creatinine was determined in plasma using creatinine liquid reagents (end-point, colorimetric, DIAZYME). The blood samples immediately after collection were spun down at 5000 rpm for 10 minutes. The plasma was then decanted and stored at -20°C until the time of creatinine determination using manufacturer's instruction. Plasma concentration of creatinine (mg.dLThe concentration of ET-1 was determined in plasma. The blood samples were collected in plastic tubes containing EDTA (1 mg/mL) before euthanasia. The sample was centrifuged at 3,000 × g for 15 min at 4°C and plasma was separated and assayed for ET-1. Plasma was acidified adding an equal volume of 20% acetic acid. ET-1 like material was extracted from plasma  using C-X (nitrate + nitrite) was determined in plasma, thoracic aorta, kidney cortex and medulla. Blood (500 μL) was collected and 40 μL of heparin was added to each sample to prevent clotting. The blood sample was then decanted and stored at -20°C until the time of nitric oxide byproducts, (NO2 + NO3) NOx, determination. To determine the NOx level of thoracic aorta, kidney cortex and kidney medulla, those tissue samples were harvested from each experimental rat and immediately homogenized with cold phosphate buffered saline (PBS) on ice, which inhibited the activity of NOS ex vivo. The homogenate was centrifuged (3000 × g, 5 min) and the supernatant was collected. The supernatant obtained from tissues and plasma was passed through a 1.2 μm multiscreen filter plate. Plasma NOx and tissue NOx concentration was determined by using Greiss reaction [2O, 20 μl 0.31 M phosphate buffer (pH 7.5) and 10 μL each of 0.86 mM NADPH (Sigma), 0.11 mM flavenidinine dinucleotide and 1.0 U/mL of nitrate reductase. NO3 was converted to NO2 by nitrate reductase (Boehriger Mannheim). Unknown tissue samples were run in duplicate. The samples were allowed to incubate for 1 hr at room temperature in the dark. Two hundred microliters of Greiss reagent [1:1 mixture of 1% sulfanilamide in 5% H3PO3 and 0.1% N-(1-naphthyl) ethyl-enediamine] were added to each well and the plates were incubated for an additional 10 min at room temperature. Absorbance was measured at 540 nm using a plate reader and converted to NOx concentration using a nitrate standard curve and expressed as μM in plasma and μmoles/g protein in tissue. Protein in the supernatant obtained from each sample was determined using standard Lowry method.The concentration of endogenous NOreaction ,15. 6 μLPreproET-1, iNOS, eNOS, total and phosphorylated p38-MAPK and ERK protein expressions of thoracic aorta, kidney cortex and kidney medulla were determined using standard SDS-PAGE and immunoblot technique. Briefly, thoracic aorta, kidney cortex and kidney medulla tissues were homogenized in lysis buffer and centrifuged as described by Pollack et al. . The supAll the data were expressed as mean ± SEM. One-way ANOVA was performed to analyze the hemodynamic and biochemical data using SPSS software. Following a significant F value, a post hoc Students Newman Keuls test was performed for inter- and intra-group comparisons. Statistical significance was realized at p ≤ 0.05 to approve the null hypothesis for individual parameters.All control rats were freely moving in their individual cages through out the study. Although diabetic rats appeared to be lethargic and displayed restricted movements, there was no sign of infection or motor disorder in any of the rats studied. The food intake and water intake of 14-days and 28-days diabetes groups were significantly increased as compared to control group  on aortic and renal ET-1 biosynthesis we determined the concentration of ET-1 in plasma and expression of ET-1 precursor, preproET-1 in thoracic aorta, kidney cortex and kidney medulla. A significant elevation in plasma ET-1 concentration was observed in 28-days diabetes as compared to 14-days diabetes and control groups Fig . We did A significant increase in the concentration of NOx in plasma of 28-days diabetes group as compared to the control and 14-days diabetes groups was observed Fig . The NOxA significant up-regulation of eNOS and iNOS in thoracic aorta in 14-days and 28-days diabetes groups was obtained as compared to control group Fig . Also inTotal p38-MAPK and phosphorylated p38-MAPK protein expressions in thoracic aorta were significantly elevated in 14-days and 28-days diabetes groups as compared to control group Fig . ExpressA significant decrease in the expression of phosphorylated ERK 1/2 of thoracic aorta in 28-days diabetes group but not in 14-days diabetes group was observed as compared to control group. We found that total ERK 2 but not total ERK 1 was significantly increased in thoracic aorta in 14-days diabetes groups as compared to control group. There was no change in the expression of total ERK 1 in 14-days and 28-days diabetes groups and ERK 2 in 28-days diabetes group as compared to control group Fig . In kidntype 2 diabetes in various animal models. This well-established model is characterized by insulin deficiency associated with insulin resistance [et al. [STZ has long been used as a drug of choice to induce sistance . It was sistance . In the  [et al.  found thRenal hypertrophy can be detected as early as one day after the onset of diabetes and seen regularly post 60-hr of single STZ injection . It has et al. [ET-1, a potent vasoconstrictor peptide, has been implicated in diabetes and cardiovascular disorders. Elevated, unchanged and attenuated plasma ET-1 levels have been reported during diabetes -27. Althet al.  followinet al. -30. In tet al.  or lack et al. .et al. demonstrated that ET-1 via binding to ETB receptors produces activation of NOS [et al. [et al. [B receptors via elevated ET-1 mechanisms. However, further studies will be required to strengthen this speculation.Hirata n of NOS  and gene [et al.  demonstr [et al. ,35. Incr [et al. . In a pr [et al. . We alsoet al. [et al. [Hyperglycemia has been shown to phosphorylate ERK1/2 in rat glomerular and mesangial cells  and p38-et al.  and Tian [et al.  demonstrin vivo and in vitro results suggest that ERK and p38MAPK may be involved in high-glucose-induced cellular hypertrophy [et al. [et al. [Both ertrophy . In the  [et al. . We spec [et al.  where thThe results obtained in the present study characterize the STZ (60 mg/kg, I.V.)-induced diabetic rat model in our laboratory. The marked characteristics of diabetic rat model include weight loss, increase food and water intake, and bradycardia. STZ-induced diabetes, both at 14-days and 28-days, produced renal dysfunction and vascular dysfunction that correlated well with levels of ET-1 and NOx and expression of preproET-1 and NOS proteins in kidney cortex and thoracic aorta. The data obtained in the present study demonstrate that progression of diabetes from 14-days to 28-days caused a factorial increase in p38-MAPK phosphorylation along with NOS upregulation in kidney cortex and thoracic aorta. The study provides evidence that diabetes produces vascular and renal dysfunction with a profound effect on signaling mechanisms at later stage of diabetes. However, more studies will be required to further delineate the inherent link or interaction between p38-MAPK upregulation, ET-1 and NO mechanisms and development of renal and vascular dysfunction during diabetes.


The origin of Borneo's elephants is controversial. Two competing hypotheses argue that they are either indigenous, tracing back to the Pleistocene, or were introduced, descending from elephants imported in the 16th–18th centuries. Taxonomically, they have either been classified as a unique subspecies or placed under the Indian or Sumatran subspecies. If shown to be a unique indigenous population, this would extend the natural species range of the Asian elephant by 1300 km, and therefore Borneo elephants would have much greater conservation importance than if they were a feral population. We compared DNA of Borneo elephants to that of elephants from across the range of the Asian elephant, using a fragment of mitochondrial DNA, including part of the hypervariable d-loop, and five autosomal microsatellite loci. We find that Borneo's elephants are genetically distinct, with molecular divergence indicative of a Pleistocene colonisation of Borneo and subsequent isolation. We reject the hypothesis that Borneo's elephants were introduced. The genetic divergence of Borneo elephants warrants their recognition as a separate evolutionary significant unit. Thus, interbreeding Borneo elephants with those from other populations would be contraindicated in ex situ conservation, and their genetic distinctiveness makes them one of the highest priority populations for Asian elephant conservation. Comparison between DNA sequences of Borneo elephants with those of other Asian elephants settles a longstanding dispute about the origins of these endangered animals Elephants have a very limited distribution in Borneo, being restricted to approximately 5% of the island in the extreme northeast . There aPopular belief holds that elephants presented to the Sultan of Sulu in 1750 by the East India Trading Company and subsequently transported to Borneo founded the current population . These aConversely, if elephants occurred naturally on Borneo, they would have colonised the island during Pleistocene glaciations, when much of the Sunda shelf was exposed  and the Elephas maximus borneensis) based on morphological differences from other populations  to 0.020 (haplotype BE), with a mean of 0.014. Assuming a nucleotide substitution rate of 3.5% per million years for the elephant mtDNA d-loop , including the hypervariable left domain of the d-loop , from 20A d-loop , the obsEMX-2) to 11.0 (LafMS03) (x¯, SE = 4.60, 1.51); the average number of alleles across loci, per population (excluding Borneo), from 2.0 (Sumatra) to 3.6 (Sri Lanka) (x¯, SE = 2.93, 0.155); the observed heterozygosity H0 across all populations (excluding Borneo) from 0.38 (EMX-4) to 0.63 (LafMS03) (x¯, SE = 0.44, 0.041); and gene diversity from 0.39 (EMX-4) to 0.69 (LafMS03) (x¯, SE = 0.47, 0.050). Comparatively, all indices demonstrated very low genetic diversity in the Borneo population: proportion of polymorphic loci, 0.4; number of alleles per locus, 1–2 (x¯, SE = 1.40, 0.219); gene diversity, 0–0.13 (x¯, SE = 0.04, 0.024); heterozygosity H0 = 0–0.07 (x¯, SE = 0.01, 0.013). The number of alleles, observed heterozygosity, and gene diversity, averaged across Asian elephant populations, were all higher than those in Borneo, at all loci (STF 0.32–0.63 (x¯, SE = 0.44, 0.034) (x¯, SE = 0.51, 0.175), and maximum-likelihood ratios of the most-likely (Borneo) to the next-most-likely population ranged from 2.97 to 48.20 (x¯, SE = 25.02, 8.795). Borneo was significantly more likely to be the source than any other population for all five genotypes, since each of the assignment likelihoods to Borneo fell outside the upper end of the corresponding distribution of assignment likelihoods to the other populations. Assignment likelihoods to the putative Indian, Sumatran, and peninsular Malaysian source populations were very small , indicating that Borneo's genotypes were highly unlikely to have originated from any of these populations.We also genotyped 15 Borneo elephants for five polymorphic autosomal microsatellite loci  and compall loci . Similarall loci . Five un, 0.034) . In test, 0.034)  or mode-, 0.034) , charactmtDNA evidence supports an indigenous hypothesis in three ways. First, this hypothesis assumes an ancient, independent evolution of Borneo's elephants, resulting in the unique, divergent Borneo haplotype(s), as we observed. Conversely, the introduction hypothesis assumes an introduction at 500 years ago or less, which approximates zero time on a scale of mtDNA d-loop evolution, and hence requires Borneo and source population haplotypes to be identical. This was not observed. Second, the estimated divergence time between the Borneo haplotype and other Asian elephant haplotypes is concordant with a mid- to late-Pleistocene isolation of elephants on Borneo and the vicariant history of the island . Third, Microsatellite data also support the indigenous hypothesis. If the Borneo population originated from animals introduced in the 16th–18th centuries, it would have reached its mid-20th-century size of approximately 2,000 individuals  in fewerF statistics  sequences from zoo animals in the United States were used as an out-group. Genetic distances among sequences were calculated using uncorrected p distances. Maximum-parsimony analysis was conducted using a heuristic search with random stepwise addition of taxa, tree bisection/reconnection branch swapping, and equal weighting; neighbour joining, with Kimura two-parameter distances; and maximum likelihood, using empirical base frequencies and estimated values for the shape parameter for among-site rate variation and transition/transversion ratios. A network of haplotypes was created using statistical parsimony in the software TCS version 1.13 . Sequences were deposited in GenBank (accession numbers AY245538 and AY245802 to AY245827). Phylogenetic analyses were conducted using PAUP* version 4.0 . Three Aion 1.13 .EMX-1 to EMX-4 (LafMS03 (Samples were screened with five published microsatellite loci, to EMX-4  and LafM(LafMS03 . Forward(LafMS03 , and 1 μ(LafMS03 .STF, using the program Arlequin version 2 (Deviations from Hardy–Weinberg equilibrium for each locus and population were tested using the exact Hardy–Weinberg test as implemented in GENEPOP 3.2 , with thersion 2 .Evidence for a recent bottleneck in the Borneo population in terms of a heterozygote excess  or a modAssignment tests were performed using WHICHRUN version 4.1 . AssuminThe GenBank accession numbers for the sequences reported in this paper are AY245538 and AY245802 to AY245827.


However, the significance of an increase in cAMP produced by α1A-AR stimulation on proliferation, hypertrophy and differentiation in these cells is not known.Fibroblasts, as connective tissue cells, are able to transform into another cell type including smooth muscle cells. α1A-AR in rat-1 fibroblasts by phenylephrine (PE) inhibited DNA synthesis by 67% and blocked the re-entry of 81% of the cells into S phase of the cell cycle. This cell cycle blockage was associated with hypertrophy characterized by an increase in protein synthesis (64%) and cell size. Elevation of cAMP levels decreased both DNA and protein synthesis. Inhibition of adenylyl cyclase or protein kinase A reversed the antiproliferative effect of cAMP analogs but not PE; the hypertrophic effect of PE was also not altered. The functional response of rat-1 cells to PE was accompanied by increased expression of cyclin-dependent kinase (Cdk) inhibitors p27kip1 and p21cip1/waf1, which function as negative regulators of the cell cycle. Stimulation of α1A-AR also upregulated the cell cycle regulatory proteins pRb, cyclin D1, Cdk 2, Cdk 4, and proliferating cell nuclear antigen. The antiproliferative effect of PE was blocked by p27kip1 antisense but not sense oligonucleotide. PE also promoted expression of smooth muscle cell differentiation markers  as well as the muscle development marker MyoD.Activation of the α1A-AR promotes cell cycle arrest, hypertrophy and differentiation of rat-1 fibroblasts into smooth muscle-like cells and expression of negative cell cycle regulators by a mechanism independent of the cAMP/PKA signaling pathway.Stimulation of α Both pharmacological and molecular cloning studies have indicated the existence of multiple subtypes of α1-ARs including α1A/C-AR, α1B-AR, and α1D-AR [1-ARs play a key role in a variety of physiological processes, such as contraction of vascular and cardiac muscle, contraction of the spleen, liver glycogenesis, or melatonin secretion in the pineal gland [1A-AR promotes hypertrophy of cardiac myocytes [1-AR are also expressed in rat aortic adventitial fibroblasts and vascular smooth muscle cells (SMC) [1A-AR stimulation in uninjured aorta whereas norepinephrine stimulated proliferation of adventitial fibroblasts through the α1B-AR subtype [Alpha1-adrenergic receptors   and theils (SMC) ,9. Howev subtype .1-AR and have been used for stable transfection of different subtypes of α1-AR to study their respective functions. However, a recent study showed the expression of a functional α1A-AR in primary tendon fibroblasts [1-AR, phenylephrine (PE), an α1-AR agonist, activates phospholipase D and releases arachidonic acid [1-ARs in rat-1 cells also increases cAMP levels and PKA activity [1A-AR is more efficiently coupled to phospholipase D activation, arachidonic acid release and cAMP than α1B-AR or α1D-AR in these cells [1A-AR expressed in COS-7 and HeLa cells [1B-AR or α1D-AR in COS and CHO cells [1B-AR, PE causes cell scattering and inhibits proliferation through activation of MAP kinases [Nonvascular fibroblasts, including cardiac fibroblasts ,10, generoblasts . In rat-nic acid . Howeveractivity . α1A-AR se cells . ActivatLa cells  and α1B-HO cells  also inc kinases .1A-ARs in CHO cells inhibits basal and growth factor-stimulated DNA synthesis, in contrast to the α1D-AR [1A-AR stimulation [1A-AR with PE in rat-1 cells affects their growth and/or differentiation status. To test this hypothesis, we have investigated the effect of PE and cAMP modulators on proliferation, growth and morphology in rat-1 cells expressing α1A-ARs. Moreover, we have examined the effect of PE and cAMP modulators on the expression of cell cycle regulators and muscle cell markers, because of the ability of fibroblasts to differentiate into myofibroblasts. Our results show that activation of α1A-ARs in rat-1 cells exerts profound effects promoting hypertrophy and expression of specific smooth muscle cell markers. We also show here that α1A-AR-induced cessation of DNA synthesis is independent of cAMP and involves the expression of cyclin-dependent kinase (Cdk) inhibitor, p27kip1.The family of connective tissue cells includes fibroblasts, cartilage cells, bone cells, fat cells and smooth muscle cells. Fibroblasts seem to be able to transform into any of other members of the family – in some cases reversibly – although it is not clear whether this is a property of a single type of fibroblast that is pluripotent or of a mixture of distinct types of fibroblasts with more restricted potentials. These transformations of connective tissue cell type are regulated by the composition of the surrounding extracellular matrix, by cell shape, and by hormones and growth factors . Heterole α1D-AR . A recenmulation . Therefo1A-AR expressed 288 ± 2 fmol/mg protein of receptors [3H]thymidine. PE decreased basal [3H]thymidine incorporation in a concentration-dependent manner with a maximum effect at 10 μM PE , even after 48 h of serum-deprivation , a β-AR antagonist , had no effect on the decrease in basal [3H]thymidine or the increase in [3H]leucine incorporation in rat-1 cells caused by exposure to PE. These results show that PE stimulates protein synthesis and inhibits DNA synthesis in rat-1 cells through activation of α1A-ARs. The hypertrophy index, an indicator of cellular hypertrophy, is defined as the ratio of protein synthesis ([3H]leucine incorporation) to DNA synthesis ([3H]thymidine incorporation) [Stimulation of αle cells  and in ale cells  increase 64% Fig  and decrtake Fig , as shownist Fig , or yohioration) . At 18 h1-AR stimulation was time-dependent and remained significant from 6 to 72 h of exposure with PE  and then treated them with PE (5 μM) or FN (1 μM) for different time periods. SQ22536 reversed the morphological changes produced by FN and restored the normal fibroblast shape, whereas it enhanced the effect of PE, i.e. the cells became more hypertrophic.Although both PE and FN inhibited DNA synthesis in rat-1 cells, they produced different effects on cell morphology. PE increased, whereas FN decreased, the apparent size of rat-1 cells as shown in Fig kip1 and p21cip1/waf1 play an important role in cell-cycle regulation [kip1 and p21cip1/waf1 in quiescent (G0) cells decline upon induction of mitogenesis [1A-AR stimulation increased the expression levels of p27kip1 (642% of control at 48 h) and p21cip1/waf1 (935% of control at 48 h)  more efficiently than p21cip1/waf1(87% of control at 24 h) suggesting a greater contribution of p27kip1 to PE-induced cell cycle arrest and a delayed induction of p21cip1/waf1. Retinoblastoma protein (pRb) hyperphosphorylation and subsequent release of E2F is required for cell cycle progression [Cyclin-dependent kinase (cdk) inhibitors p27gulation ,26. High h) Fig. . The progression . Howevergression . Our reskip1 level is a critical determinant of the cell response, hyperplasia vs. hypertrophy, to angiotensin II and other growth factors [kip1. PE upregulates the expression of p27kip1 at 18 h of treatment in rat-1 cells at all concentrations , but not sense ODN , diminished p27kip1 level , which normally do not change even during mitogenic stimulation.We next investigated the effect of PE on several cell cycle proteins important for G1A ARs promoted a change in morphology associated with hypertrophy, we examined the effect of PE on expression of the specific smooth muscle cell markers, α-smooth muscle actin (SMα actin), caldesmon and myosin heavy chain (SM-MHC) [1A ARs with PE (5 μM) promoted a time-dependent increase in the levels of SMα actin (695% of control at 24 h)  . The smo4 h) Fig , caldesm4 h) Fig  and SM-M4 h) Fig  as shownrest Fig . The exprest Fig . The α1A-MHC Fig . MyoD ex-MHC Fig . The lev1A-AR subtype to promote differentiation of a fibroblast into a SMC/myocyte-like cell. Further, it demonstrates that α1A-AR-induced cell cycle arrest and hypertrophy as well as differentiation is mediated through a mechanism dependent upon the increased expression of the critical cell cycle protein p27kip1 and selective smooth muscle markers.This study is the first demonstration of the ability of an α1A-ARs promotes hypertrophy of cardiac myocytes [1A-AR stimulation in uninjured aorta [1A-AR, PE stimulates cell scattering and inhibition of proliferation [1A-ARs [1A-ARs in rat-1 cells expressing this subtype. Analysis of the effect of α1A-AR stimulation on cell cycle progression revealed that it inhibits the re-entry of cells from G0/G1 into the S phase of the cell cycle.Stimulation of αmyocytes . Norepined aorta . In HepGferation . Similar [1A-ARs ,18. In t1A-AR-induced cell cycle arrest, hypertrophy and differentiation of rat-1 cells. Previous studies have shown that in rat 1-cells expressing α1A-ARs, PE promotes increase in cAMP accumulation and PKA activation [1A-AR stimulation. However, activation of the cAMP/PKA pathway did not promote hypertrophy or differentiation of rat-1 cells. Moreover, inhibition of cAMP/PKA did not reverse the α1A-AR-induced inhibition of DNA synthesis. Therefore, α1A-AR-induced cell cycle arrest, hypertrophy and differentiation, is independent of the cAMP/PKA pathway in rat-1 cells. Recently, the cAMP pathway has been implicated in α1A-AR-induced cell cycle arrest in CHO cells expressing α1A-ARs [1A-AR stimulation on CHO cells hypertrophy and differentiation is not known. During our investigation of the possible mechanism by which PE induces cell cycle arrest, we observed that although both PE and FN inhibited DNA synthesis, these two agents produced remarkably different morphological changes in rat-1 cells. FN promoted a change in rat-1 cells to a small, shrinked, round shaped morphology whereas PE shifted the cells to a hypertrophied, enlarged and spindle shaped smooth muscle-like phenotype. This α1A-AR-induced morphological change was again independent of cAMP. Differences between PE and cAMP on different cell functions are reported in Table Next we attempted to define the mechanism mediating αtivation . Since ctivation , it seem α1A-ARs . The dif α1A-ARs  vs. PE-i α1A-ARs . In addi1A-AR stimulation and cAMP on rat-1 cell hypertrophy and morphology led us to explore the effects of PE and FN on different cell parameters associated with morphological changes, i.e. cell cycle regulators and smooth muscle cell differentiation markers. Recently, it has been reported that the Cdk inhibitor p27kip1 mediates angiotensin II-induced cell cycle arrest and hypertrophy in cultured renal tubular cells [1A-ARs increased the expression of p27kip1 to a much greater extent than p21cip1/waf1, suggesting an important role for the former Cdk inhibitor in the action of α1A-AR stimulation. Interestingly, the time of upregulation of p27kip1 by PE correlated closely with its effect on inhibition of DNA synthesis, which was maximal at 18 h. Depletion of p27kip1 prevented both PE-induced upregulation of p27kip1 and reversed PE-induced decrease in DNA synthesis. Therefore, p27kip1 plays a central role as a mediator of α1A-AR-induced inhibition of DNA synthesis and probably hypertrophy and differentiation of rat-1 fibroblasts.The different effects of αar cells , and vasar cells  and induar cells . In the 1A-ARs shifted rat-1 fibroblasts to SMC/myocyte-like phenotype, it also increased the expression of the helix loop helix protein MyoD, a skeletal muscle-specific regulatory transcription factor [kip1. MyoD has been shown to interact with pRb and to promote muscle gene activation and cell cycle arrest [An important finding in the present study was that PE produced a change in the morphology of rat-1 cells characterized by an increase in cell size. Supporting this phenotypic and hypertrophic change was our demonstration that PE increased global protein synthesis and the expression of markers specific to smooth muscle cells such as smooth muscle actin, caldesmon, and myosin heavy chain. The protein levels of these smooth muscle cell markers were found to remain elevated for up to 48 h, consistent with the PE-induced morphological change that persisted for the same time period. Although stimulation of αn factor . Surprise arrest ,36. Indee arrest . More ree arrest . Althouge arrest . Therefoe arrest .1/S phase progression [1A-ARs promotes the transcriptional/translational activation of the machinery required for G1/S cell cycle progression. However, a simultaneous increase in Cdk inhibitors such as p27kip1 prevented DNA synthesis. Elevation of p27kip1 protein level alone is sufficient for induction of cell cycle arrest, independent of cyclins or Cdk level [PE-induced hypertrophy and differentiation of rat-1 cells was also associated with increased levels of cell cycle proteins pRb, cyclin D1, PCNA and Cdk2 that are important for Ggression . These ddk level . Surprisdk level ,26. Cdk 1A-AR promotes the up-regulation of Cdk inhibitors (p27kip1, p21cip1/waf1), smooth muscle cell markers, MyoD, and G1/S transition cell cycle proteins (pRb, cyclin D1, PCNA, Cdk2/4) leading to inhibition of proliferation and stimulation of hypertrophy and differentiation is not known. The cAMP/PKA pathway was excluded by our results as well as the ERK pathway [1A-AR, epinephrine (one hour stimulation) increased the gene expression of IL-6, gp-130  and STAT-3 (an IL-6 activated transcription factor) [1A-adrenergic receptor, epinephrine also increased IL-6 secretion and STAT-3 Ser727 phosphorylation [1A-AR activation in rat-1 cells.The mechanism by which stimulation of the α pathway . The pho pathway . Recentl factor) . Moreoverylation . Therefoin vivo, our model uses a transformed embryonic fibroblast cell line that expresses high levels of α1A-AR [1A-AR.With regard to functional significance f α1A-AR . Therefo1A-ARs in rat-1 cells promotes cell cycle arrest by increasing levels of Cdk inhibitors and promotes hypertrophy and differentiation into a phenotype having the characteristics of smooth muscle cells by a mechanism independent of cAMP or EGF. Moreover, cell cycle progression was blocked at G1/S transition without causing apoptosis, and this cycle arrest was critical for rat-1 cell hypertrophy and differentiation. Reducing p27kip1 levels reversed α1A-AR-promoted inhibition of DNA synthesis. Furthermore, it shows that cell cycle arrest and differentiation are closely coordinated processes but temporally separable. Further studies are underway in our laboratory to characterize the signaling pathway(s) involved in α1A-AR-induced differentiation of fibroblasts to smooth muscle cells.This study demonstrates that stimulation of α3H]thymidine (20 Ci/mmol) was purchased from NEN Life Science Products, Inc. (Boston, MA). L-[4,5-3H] leucine from Amercham Pharmacia Biotech. (Piscataway, NJ.). L-phenylephrine hydrochloride, penicillin, streptomycin, prazosin, propranolol, epidermal growth factor (EGF), and propidium iodide were obtained from Sigma (St. Louis, MO). Forskolin (FN), 8-cpt-cAMP and SQ 22536 were purchased from Calbiochem (La Jolla, CA). 2'-5'dideoxyadenosine and 2'-deoxyadenosine 3'-monophosphates were purchased from Biomol (Playmouth Meeting, PA). G418 sulfate from Invitrogen (Carlsbad, CA). Hanks' balanced salt solution and fetal bovine serum were from Mediatech, Inc. (Herndon, VA). Dulbecco's Modified Eagle's Medium (DMEM) and trypsin/EDTA were obtained from Life Technologies Inc. (Grand Island, N.Y).[Methyl-1A-AR kindly provided to us by Drs. L. Allen, R. J. Lefkowitz, and M. G. Caron (Duke University), were maintained in DMEM supplemented with 10% (v/v) fetal bovine serum, 400 μg/ml G418 sulfate, 50 μg/ml streptomycin and 50 units/ml penicillin at 37°C in an humid atmosphere (5% CO2, 95% air). Cells were serially passaged upon reaching confluence, and all experiments were performed on subculture passages 5–15. Prior to all experiments, preconfluent cell cultures were serum-starved for 48 h.Rat-1 cells transfected with bovine α3H]thymidine incorporation. Inhibition of [3H]thymidine incorporation was used as a quantitative measure of reduction in DNA synthesis. Cells were serum-starved in the presence or absence of agonists for the indicated time period, and [3H]thymidine (0.5 μCi/ml) was added for the last 4 h of the incubation. This time period was chosen because it gave the maximum incorporation of [3H]thymidine into DNA after addition of agonists. The medium was then removed, and the cells were washed twice with phosphate-buffered saline and three times with 10% ice-cold trichloroacetic acid. Cells were kept in contact with trichloroacetic acid for 10 min during each wash. The precipitated material was dissolved in 1 M NaOH containing 0.1% SDS, and radioactivity was determined by liquid scintillation spectrometry.Cells at a density of 150,000 cells/well were seeded in DMEM containing 10% FBS on 24-well plates until they reached 80–90% confluency and were serum-deprived for 48 h prior to the addition of agonists. Rat-1 cells, even after serum-deprivation for 2 days, exhibit a measurable level of [3H]leucine was added for the last 4 h of each incubation with or without the indicated concentrations of the agonists. Cells were fixed and washed three times with ice-cold trichloroacetic acid (10%). The precipitated material was solubilized with 0.1 M NaOH and the incorporated radioactivity was counted by liquid spectrometry.Rat-1 cells were seeded at a density of 150,000 cells/well in 24-well plates and just prior to confluency were serum-deprived for 48 h. Cells were rinsed with DMEM and 1 μCi/ml [Flow cytometry studies were performed to determine the effect of different concentrations of PE on cell cycle phases. Cells were subjected to flow cytometric DNA analysis as described  with somPreconfluent cultures were serum-starved for 48 h. Cells were incubated with different concentrations of PE, FN and 8-cpt-cAMP for 18 h, trypsinized with 1 ml trypsin/EDTA for 5 min and centrifuged for 10 min at room temperature. The pellet was resuspended in 1 ml plain DMEM. 10 μL of the suspension was mixed with 10 μL of 0.4% trypan blue in a 0.5 ml microtube. The total number of cells and the number of blue cells and the percentage of the viable cells in 10 μL of the trypan blue mixture was calculated as follows: % viable cells = [1-] × 100.Rat-1 cells resuspended in culture medium were seeded on six-well plates (Corning, N.Y.). Preconfluent cells were serum-deprived for 2 days, pre-incubated with inhibitor (s) for 30 min, and then stimulated with 5 μM PE and /or 1 μM FN for the indicated time. Cells were rinsed twice in PBS to remove non-adherent cells and then fixed for 10 min in [1:1] methanol-acetone mixture at room temperature. Cells were washed once in distilled water and stained in hematoxylin solution (Sigma, St. Louis, MO) for 15 min at room temperature. Cells were again washed three times in water, air dried and were finally observed under a phase contrast microscope. Images were captured and saved as TIFF files. For each condition, data were collected by random observation. Hypertrophic phenotype was defined as both enlarged, elongated and spindle-shaped whereas rat-1 fibroblasts are round and/or polygonal-shaped cells.kip1 experiments, phosphorothionate oligonucleotides (ODN) (Life Technologies, Grand Island, N.Y.) were used. The antisense ODN sequence used in the experiments was 5'-CACTCTCACGTTTGACAT-3' (nuc 1–18 of rat p27 kip1); the sense ODN sequence was 5'-ATGTCAAACGTGAGAGTG. ODN transfection was performed with oligofectamine in Opti-MEM according to the manufacturer's protocol (Invitrogen, Carlsbad, CA). Cells were left in the transfection mixture for 48 h and then incubated for 24 h with or without agonists and harvested for Western blot, or labeled with [3H]thymidine to determine DNA synthesis.To determine whether protein kinase A (PKA) mediates the antiproliferative effect of PE, rat-1 cells were transiently transfected with πLXX-PKI ,24, a plkip1, p21waf1/cip1, pRb ; caldesmon (smooth muscle), myosin (smooth muscle), α-smooth muscle actin, β-actin (Sigma Biosciences); MyoD, cyclin D1, Cdk 2, Cdk 4, PCNA, lamin A/C or vimentin (Santa Cruz Biotechnology). Following incubation, the membranes were washed three times 10 min each in TBST and incubated with a secondary antibody coupled to peroxidase for 1 h at room temperature. Then the membranes were washed three times 10 min each in TBST. Specific proteins were detected by enhanced chemiluminescence  according to the manufacturer's instructions and analyzed with an Alpha Innotech Fluorochem imaging system (Packard Canberra). A lysate from cultured aortic vascular smooth muscle cell (VSMC) was used as a control for the expression of smooth muscle markers.Cells were rinsed twice with PBS and lysed in ice-cold lysis buffer . Lysates were centrifuged at 4°C for 15 min in a microfuge at maximum speed, and the supernatant was collected for Western blot analysis. Equal amounts of protein were separated on denaturing SDS/polyacrylamide gel and transferred on nitrocellulose blots  by electrophoresis. Blots were blocked for 1 h in 5% nonfat dry milk in TBST, washed three times 5 min each in TBST and then incubated with the indicated specific primary antibody overnight at 4°C: p273H]thymidine and/or leucine were variable in different batches of cells. However, the effect of various agents on the incorporation of [3H]thymidine and [3H]leucine in rat-1 cells was consistent within each batch of cells. The results are expressed as mean ± SEM. The data were analyzed by one-way analysis of variance; the Newman-Keuls multiple range test was applied to determine the differences among multiple groups, the unpaired Student's t-test was applied to determine the difference between two groups. The null hypothesis was rejected at p < 0.05. The protein level were estimated by densitometric analysis of the Western blots and performed on the indicated number of blots using NIH Image software, and expressed as a percentage of the control, arbitrarily chosen as 100%.The basal values of incorporation of [AR, adrenergic receptor; Cdk, cyclin-dependent kinase; FN, forskolin; MHC, myosin heavy chain; PCNA, proliferating cell nuclear antigen; PE, phenylephrine; pRb, retinoblastoma protein; SMC, smooth muscle cellAES performed thymidine/leucine incorporation, morphological studies, cell viability, flow cytometry and Western blot analysis. JHP carried out the antisense design, transfection experiments, statistical analysis and some thymidine/leucine incorporation and Western blot analysis. KUM conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.