Heteractis crispa (Radianthus macrodactylus) was determined by protein sequencing and cDNA cloning. InhVJ amino acid sequence was shown to share high sequence identity (up to 98%) with the other known Kunitz-type sea anemones sequences. It was determined that the P1 Thr at the reactive site resulted in a decrease of the Ki of InhVJ to trypsin and α-chymotrypsin . By structure modeling the functional importance of amino acids at the reactive site as well as at the weak contact site were determined. The significant role of Glu45 for the orientation and stabilization of the InhVJ-trypsin complex was elucidated. We can suggest that there has been an adaptive evolution of the P1 residue at the inhibitor reactive site providing specialization or functional diversification of the paralogs. The appearance of a key so-called P1 Thr residue instead of Lys might lead to refinement of inhibitor specificity in the direction of subfamilies of serine proteases. The absence of Kv channel and TRPV1-receptor modulation activity was confirmed by electrophysiological screening tests. The primary structure of a new Kunitz-type protease inhibitor InhVJ from the sea anemone  Protein inhibitors regulate the activity of proteases involved in biochemical processes such as blood clotting, complement system, digestion, inflammation, apoptosis and others. In the case of protease inhibitor deficiency, some diseases may appear. Currently some attempts have been made in the therapeutic application of protease inhibitors ,2,3. TheBesides neurotoxins, pore-forming toxins, and phospholipases A2, sea anemones also contain a large amount of protease inhibitors. To date about 40 low molecular mass protease inhibitors 6000 Da) from sea anemones have been isolated and partially characterized 000 Da fr,21,22,23Stichodactyla helianthus has broad protease specificity and inhibits not only trypsin and chymotrypsin but also human neutrophil elastase (HNE), papain, and pepsin , the complete amino acid sequence of InhVJ  was deduced. InhVJ consists of 56 amino acid residues and has a molecular mass according to the sequence analysis equal to 6112 Da. Since the molecular mass determined by MALDI-TOF/MS is 6106 Da, the difference of six mass units indicates that all six cysteine residues are involved in three disulfide bonds. The full-length cDNA encoding InhVJ was successfully obtained by combination of 3′ and 5′RACE techniques. It should be noted that the transcript corresponding to the full-length InhVJ was one of the most abundant transcripts (13.5%). The full-length cDNA includes 427 bp with an open reading frame of 234 bp, which encodes a polypeptide of 78 amino acid residues. The signal peptide is composed of 22 amino acid residues. The mature polypeptide (56 aa) is identical to the sequence obtained by Edman degradation . H.crispa. It also shares a high degree of homology with HCGS-polypeptides recently deduced by the PCR-based cloning technique . The InhVJ-like subset includes molecules with neutral or slightly positive total charges ranging from +0.02 to +1.03, while the APHC1-APHC3-like subset contains molecules with more positive charges ranging from +1.81 to +2.15. We can suggest that there has been an adaptive evolution of the P1 residue at the inhibitor reactive site providing specialization or functional diversification of the paralogs. On the one hand, the appearance of the Thr P1 residue instead of Lys might lead to refinement of inhibitor specificity in the direction of subfamilies of serine proteases. On the other hand, it also might lead to the appearance of polypeptides with, for instance, a new function such as TRPV1 modulation.Type 2 toxins from sea anemones are known to be potent inhibitors of voltage-gated potassium channels. Kalicludines block Kv1.2 channels with an IC50 value of about 1 µM , SHTX IIAs for InhVJ’s ability of blocking TRPV1-receptor activity, electrophysiological analysis revealed no activity of InhVJ in a concentration of up to 10 µM . Oocytes expressing TRPV1 channels were, without pre-incubation, exposed to 10 µM of InhVJ in the presence of 2 µM capsaicine for time intervals ranging from 10 to 60 s. No significant effect was observed (p < 0.03). APHC1 was shown to modulate TRPV1-receptor with an EC50 value of about 54 nM and inhibit capsaicin-induced currents (32% ± 9%) [21]. InhVJ and APHC1-APHC3 shared 91% to 96% sequence identity. The main difference between the polypeptide sequences was the substitution of His48Arg, which is important for TRPV1 modulation activity . So the experimental data is in complete agreement with the results of phylogenetic analysis, where dividing of a cluster into two subsets of InhVJ-like and analgesic polypeptides occurs. These results also confirm our suggestion that there is a functional specialization of InhVJ to only protease inhibition during evolution.Ki in the range 1011–1014 M). BPTI Lys14 (the numbering is based on the sequence of InhVJ) P1 amino acid residue located at the center of the canonical binding loop plays an important role in the formation of stable complexes with proteases. The side chain of Lys14 penetrates deeply into the active site of trypsin and forms electrostatic interactions with its Asp189. It has been shown that the replacement of BPTI Lys14 by point mutations into other amino acid residues leads to an increase of association constant in complexes with trypsin-like proteases. It was deduced that P1 aromatic , large hydrophobic  and polar  amino acid residues form stronger complexes with trypsin and chymotrypsin than small , branched  and acidic side-chains  do [The best-studied polypeptide of the Kunitz family BPTI is a potent inhibitor of serine proteases ( Glu) do . H. crispa, A. sulcata, Rhodactis rhodostoma, S. helianthus, and A. elegantissima, like BPTI, are active towards trypsin   . However 105 М−1 . The con 105 М−1 . The conin silico investigation, Jn-IV with Thr at P1 position was hypothesized to inhibit human neutrophil elastase HNE [Serine proteases (trypsin and elastase) are known to be involved in many inflammatory processes ,46. The tase HNE . ApparenTo elucidate the functional importance of amino acid residues in the complexes of InhVJ with serine proteases we used structural modeling methods.S.helianthus SHPI-1 (PDB 1SHP) established by 1H-NMR spectroscopy [Currently, there is a unique spatial structure of the protease inhibitor from the sea anemone troscopy . The higtroscopy ,49,50 . The Ramachandran plots of φ, ψ angles  show thaN- and C-termini of the molecule, two antiparallel β-strands and two large loops (disordered structure) and is stabilized by three conservative disulfide bonds. Thus, the InhVJ structural model was accurate enough for further structural and functional studies.The content of secondary structure elements in the InhVJ structural model was determined by Molmol . The 3D-To highlight the mechanism of InhVJ interaction with serine proteases by the method of molecular docking, a structural model of InhVJ-trypsin complex was designed a. AccordKi values of their complexes  as well as at the weak contact site (three amino acids) to free binding energies for the complexes formation, were performed. According to computational data, the P1 Lys residue at the reactive site made the greatest contribution to the binding free energy for the complex formation. Whereas the contribution of the Thr residue at this position was reduced by almost half, but still quite substantial for both InhVJ and for the mutant BPTI Lys14Thr . Ki value of the InhVJ-trypsin complex. It should be noted that the presence of Tyr16 in InhVJ instead of Arg16 in BPTI was more advantageous in terms of solvation energy. One can see the decrease of the binding free energy from −3.2 Kcal/Mol for the BPTI-trypsin complex to −5.9 Kcal/Mol for the InhVJ-trypsin complex. However, this advantage was not enough to compensate the energy loss caused by the Lys to Thr replacement. In this case there was the electrostatic potential weakening in the area of the InhVJ reactive site, which apparently resulted in the decrease of the At the weak contact site of inhibitors, two residues make the main energy gain. BPTI Arg38 forms two hydrogen bonds with the Asn97 of trypsin (supplementary data), and contributes to the binding free energy by about −2.0 Kcal/Mol. At this position in the InhVJ molecule there occurs a negative charge (Glu38), which does not influence the complex binding free energy. At the same time, in the InhVJ-trypsin complex, Glu45 makes the most substantial negative contribution to the complex formation energy , unlike BPTI Lys45 with a positive contribution. The strong electrostatic attraction of Glu45 to Lys60  of the eH. crispa (R. macrodactylus) were collected in the coral reefs of the Seychelles during a marine expedition aboard the research vessel “Academik Oparin”. Dr. C. D. Grybelniy  confirmed the identity of the species. InhVJ was isolated from 70%-ethanol extract of H. crispa by the scheme, which included a hydrophobic chromatography on Polychrome-1, gel filtration chromatography on Bio-gel P-4 and ion-exchange chromatography on SP-Sephadex G-25 [18 column  with monitoring at 214 nm. Solvent A was 0.1% trifluoroacetic acid (TFA) in water, solvent B was 0.1% TFA in acetonitrile. A linear gradient from 10% to 60% of solvent B concentration was performed at a flow rate of 0.5 mL/min for 60 min. As the result of the second purification by RP-HPLC under the same conditions the individual polypeptide was obtained.Specimens of the sea anemone dex G-25 . The obt18 column  with monitoring at 214 nm. Solvent A was 0.1% TFA in water, solvent B was 0.1% TFA in acetonitrile. A linear gradient from 10 to 60% of solvent B concentration was performed at a flow rate of 0.5 mL/min for 100 min. Alkylated polypeptide was digested with trypsin  1:50 (w/w) in 300 µL of 100 mМ ammonium bicarbonate (рН 8.0) at 37 °С for 24 h. Tryptic peptides were separated and desalted by RP-HPLC. InhVJ was reduced and alkylated with 4-vinylpyridine as described in . The resMolecular weight determination of InhVJ and tryptic peptides was performed by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF/MS) in linear positive ion mode, using BIFLEX-III instrument . Sinapinic acid was used as a matrix. Angiotensin-II  and matrix peaks were used for calibration of the instrument. The amino acid sequences of tryptic peptides were determined on an automated sequencer protein «Procise 492 cLC» .H. crispa tentacles cDNA synthesized previously [The full-length cDNA of InhVJ was performed by 3′ and 5′RACE technique with eviously . The nuceviously . BrieflyEscherichiacoli Top10 strain . Plasmids were sequenced by the dideoxy chain termination method using the ABI PRISM 3130xL Genetic Analyzer . cDNA sequences were analyzed applying the CromasPro  and Vector NTI  programs. The 3′RACE (~300 bp) and the 5′RACE (~200 bp) PCR fragments were gel separated, purified and TA cloned  into Searching homology sequences analysis was carried out using protein databases and BLAST programs . PhylogeV1.1, rKV1.2, hKV1.3, rKV1.4, rKV1.5, rKV1.6, Shaker IR, rKV2.1, hKV3.1, rKV4.2, rKV4.3, hERG), and the capsaicine receptor (TRPV1) in Xenopuslaevis oocytes, the linearized plasmids were transcribed using the T7 or SP6 mMESSAGE-mMACHINE transcription kit . The harvesting of stage V-VI oocytes from anaesthetized female X. laevis frogs was previously described [2, 1.8; MgCl2, 2 and HEPES, 5 (pH 7.4), supplemented with 50 mg/L gentamycin sulfate.For the expression of voltage-gated potassium channels  or HK (in mM): NaCl, 2; KCl, 96; CaCl2, 1.8; MgCl2, 2 and HEPES, 5 (pH 7.4). Voltage and current electrodes were filled with 3 M KCl. Resistances of both electrodes were kept between 0.5 and 1.5 MΩ. The elicited currents were filtered and sampled at resp. 1 kHz and 10 kHz (for potassium currents) and at resp. 0.2 kHz and 0.5 kHz (for TRPV1 currents), using a four-pole low-pass Bessel filter. Leak subtraction was performed using a P/4 protocol. KV1.1-KV1.6 and Shaker currents were evoked by 500 ms depolarizations to 0 mV followed by a 500 ms pulse to −50 mV, from a holding potential of −90 mV. Current traces of hERG channels were elicited by applying a +40 mV prepulse for 2 s followed by a step to −120 mV for 2 s. KV2.1, KV3.1 and KV4.2, KV4.3 currents were elicited by 500 ms pulses to +20 mV from a holding potential of −90 mV. TRPV1 currents were measured in ND96 solution using a protocol of −90 mV during 400 s. The recording chamber was perfused at a rate of 2 mL min−1 with a ND-96 solution containing (in mM) 96 NaCl, 2 KCl, 1.8 CaCl2, 1 MgCl2, 5 HEPES, pH 7.4. As previously described [n ≥ 3) and are presented as mean ± standard error. Two-electrode voltage-clamp recordings were performed at room temperature (18–22 °C) using a Geneclamp 500 amplifier  controlled by a pClamp data acquisition system . Whole cell currents from oocytes were recorded 1–4 days after injection. The bath solution composition was ND96 (in mM): NaCl, 96; KCl, 2; CaClescribed , capsaicA InhVJ spatial structure model was generated by homology modeling method using SWISS-MODEL server  with the® software.The structural models of the InhVJ-trypsin as well as InhVJ-α-chymotrypsin complexes were generated using the molecular docking method by the ClusPro2.0 server resources . CrystalSea anemones are known to produce a large amount of Kunitz-type polypeptides, which can possess the feature of a protease inhibitor as well as of a modulator of Kv or TRPV1 channels. InhVJ, a new Kunitz-type inhibitor with the so-called P1 Thr residue is specific to trypsin-like proteases and does not modulate Kv or TRPV1 channels. This inhibitor forms a stable complex with trypsin and is stabilized by H-bonds of the P1 Thr residue at the reactive site with the protease active site residues, as well as via electrostatic interaction and H-bonds of Glu45 at the weak contact site with protease Lys60 and Tyr39.


Drosophila heart model to examine its role in cardiac physiology, in conjunction with RNAi-mediated gene silencing specifically in the heart in vivo. Analysis of cardiac physiology was carried out using high-speed video recording in conjunction with movement analysis algorithms. unc-45 knockdown resulted in severely compromised cardiac function in adults as evidenced by prolonged diastolic and systolic intervals, and increased incidence of arrhythmias and extreme dilation; the latter was accompanied by a significant reduction in muscle contractility. Structural analysis showed reduced myofibrils, myofibrillar disarray, and greatly decreased cardiac myosin accumulation. Cardiac unc-45 silencing also dramatically reduced life-span. In contrast, third instar larval and young pupal hearts showed mild cardiac abnormalities, as severe cardiac defects only developed during metamorphosis. Furthermore, cardiac unc-45 silencing in the adult heart (after metamorphosis) led to less severe phenotypes. This suggests that UNC-45 is mostly required for myosin accumulation/folding during remodeling of the forming adult heart. The cardiac defects, myosin deficit and decreased life-span in flies upon heart-specific unc-45 knockdown were significantly rescued by UNC-45 over-expression. Our results are the first to demonstrate a cardiac-specific requirement of a chaperone in Drosophila, suggestive of a critical role of UNC-45 in cardiomyopathies, including those associated with unfolded proteins in the failing human heart. The dilated cardiomyopathy phenotype associated with UNC-45 deficiency is mimicked by myosin knockdown suggesting that UNC-45 plays a crucial role in stabilizing myosin and possibly preventing human cardiomyopathies associated with functional deficiencies of myosin.UNC-45 is a UCS (UNC-45/CRO1/She4P) class chaperone necessary for myosin folding and/or accumulation, but its requirement for maintaining cardiac contractility has not been explored. Given the prevalence of myosin mutations in eliciting cardiomyopathy, chaperones like UNC-45 are likely to be equally critical in provoking or modulating myosin-associated cardiomyopathy. Here, we used the  These motors are critical for cellular processes such as cytokinesis, vesicle transport, cell motility, and muscle movement Drosophila UNC-45 and the yeast UCS protein She4p have been resolved; these proteins mainly consist of armadillo-like helical repeats elegans and Drosophila each contain a single unc-45 gene. C. elegans unc-45 mutants are characterized by uncoordinated movement and abnormal muscle structure Drosophila UNC-45 possesses chaperone activity that is required for myosin accumulation, and a null mutation leads to embryonic lethality C. elegans and Drosophila, vertebrates have two unc-45 genes UNC-45B, whereas the other is expressed in multiple cell types and is designated UNC-45AXenopus, UNC-45B is required for cardiac and skeletal muscle function and a deficit or mutation leads to striated muscle dysfunction, paralysis and embryonic lethality Structurally, UNC-45 is composed of three domains. The N-terminal tetratricopeptide repeat (TPR) domain is necessary for binding to HSP-90 Drosophila model to investigate UNC-45 function during metamorphosis and in adult cardiac tissue. Drosophila is an advantageous model for studying cardiac development and function since, unlike vertebrates, heart function can be significantly compromised without causing immediate death Drosophila heart is a tubular structure consisting of a single layer of contractile cardiomyocytes and non-contractile pericardial cells that align along each side of the heart wall. The heart is supported by alary muscles and, in adults, by a layer of ventral longitudinal muscle cells de novo in the first and second abdominal segments Although cardiac dysfunction and lethality are associated with inhibition of expression of the UNC-45B isoform Drosophila to study the establishment and maintenance of cardiac function associated with a myosin chaperone encoded by unc-45. Our genetic, structural and functional approaches demonstrate that UNC-45 is crucial for cardiac morphology, physiology and myosin accumulation in the myocardium. We show that unc-45 silencing in third instar larval and young pupal hearts results in mild cardiac abnormalities. However, major cardiac defects appear as a result of knockdown during metamorphosis, indicating that UNC-45 participates in the process of remodeling of the adult heart to ensure normal sarcomeric structures and contractility. Cardiac unc-45 silencing in the adult heart (after metamorphosis) leads to a less severe phenotype. Our demonstration that UNC-45 deficiency is mimicked by myosin knockdown suggests that UNC-45 plays a crucial role in stabilizing myosin and is likely involved in preventing human cardiomyopathy.Here, we describe the use of unc-45 in the Drosophila heart was carried out using the UAS-Gal4 system Hand-Gal4 driver unc-45-RNAi transgenes Hand-Gal4 mediated KD of unc-45 in hearts of 1 week old flies (Hand>UAS-unc-45-RNAi) reduced levels of UNC-45 by ∼80% compared to age-matched controls . Analysis of heart function in 1 week old Hand>UAS-unc-45 RNAi flies (referred to hereafter as unc-45 KD) revealed severe heart defects compared to controls  approach. Silencing of controls : unc-45 ife-span . Interesunc-45 caused a significant prolongation of the heartbeat length, as manifested in an increase of both systolic and diastolic intervals   . This waunc-45, control and KD hearts were probed with an antibody against myosin. Myofibrillar disarray was assessed with immunofluorescence microscopy. As shown in unc-45 KD hearts showed severe reduction in myosin content . As shown in unc-45 KD hearts compared to those in control hearts. However, actin expression remained unchanged. This is consistent with our observation with intact hearts probed with anti-myosin and phalloidin upon unc-45 KD (unc-45 KD hearts was confirmed by probing an immunoblot with myosin antibody (not shown). However, myosin expression in indirect flight muscles was similar in both control and unc-45 KD flies (not shown) confirming that the KD was specific to heart muscle.The lack of patterned myosin immunoreactivity in the myofibrils of nc-45 KD . The redunc-45 KD suggested that the ensuing heart structure and function defects were mainly the result of myosin deficiency. Therefore, we tested if KD of myosin heavy chain (Mhc) itself can reproduce an unc-45 KD-like phenotype. We evaluated flies with cardiac-specific Mhc KD using the Hand-Gal4 driver. As for cardiac unc-45 silencing, Mhc KD hearts showed prolonged systolic and diastolic intervals . The finding that cardiac Mhc or unc-45 KD produce a similar reduction in myosin abundance as well as similar cardiac structure/function phenotypes suggests that UNC-45 may be not only critical for myosin accumulation in the myocardium but also for establishing or maintaining normal myosin-dependent cardiac functionality.The decrease in myosin levels due to ntervals  and incrntervals  resultinntervals . In addintervals . In addiHand-Gal4 driver used to KD unc-45 is expressed in the heart from embryogenesis through adulthood, results of manipulations using this driver do not allow us to distinguish whether unc-45 is required during development for establishing normal heart function, or whether it is needed to maintain cardiac integrity during adulthood. Previous analyses demonstrated that during metamorphosis the Drosophila heart undergoes significant remodeling with major morphological and structural transformations unc-45 mRNA expression is progressively up-regulated in the remodeling heart during metamorphosis Hand>unc-45-RNAi hearts 1-4 days after eclosion and found that, as for hearts from 1-week or older unc-45 KD flies, cardiac function was significantly compromised compared to age-matched controls  pupae regarding cardiac contractility compared to wild type. Cardiac contractility of control and unc-45 KD young pupae is shown in unc-45 KD in third instar larvae and young pupae are shown in unc-45 KD hearts showed a small but significant increase in heart rate (tachycardia) compared to age-matched control  was depressed compared to control third instar larvae  or in young adults (after metamorphosis). Control flies were also exposed to the same temperature conditions. Conditional cardiac KD of unc-45 with the TinCΔ4-Gal4; Gal80ts starting prior to metamorphosis resulted in a severe cardiac phenotype in adult hearts  showed prolonged systolic and diastolic intervals compared to controls , dilation of the heart did not occur . This differential expression may be true for the heart as well unc-45 is not null) are sufficient to maintain cardiac contractility in the larval or young pupal hearts. Based upon these data and our cardiac phenotype, we speculate that the continued requirement for UNC-45 during later stage metamorphosis results in more severe cardiac deficits that may not permit compensatory changes in heart rate seen in larvae and young pupae. Thus, UNC-45 is critical for folding and assembly of myosin in an almost complete remodeling from the larval heart to the adult heart.The Drosophila cardiac structure and function. UNC-45 appears to be critical for myosin incorporation into sacomeres/myofibrils of the myocardium, as it is in skeletal muscles. Since this myosin chaperone is critical for maintaining the structural integrity of the cardiac contractile apparatus, it is possibly essential for human cardiac function and survival as well. Indeed, proteomic analysis of hearts from patients suffering from ischemic heart failure has detected increased levels of UNC-45, supporting the hypothesis that this chaperone may be important during human cardiac arrest Our study represents the first evidence of a role for a molecular chaperone in unc-45 (CG2708) gene were obtained from the Vienna Drosophila RNAi Center (VDRC). Each RNAi transgene was made with inverted repeat of an unc-45 fragment, driven by the UAS-promoter as previously reported nd and 3rd chromosome (stock IDs 2708R-1 and 2708R-2) for unc-45 were also obtained from the National Institute of Genetics Fly Stock Center (NIG), Tokyo, Japan. Myosin RNAi transgenes (CG17927) were also obtained from VDRC and NIG (construct IDs 1485 and 102402 from VDRC and stock ID 17927 R-1 from NIG). The cardiac tissue-specific Hand-Gal4 driver was gift from Eric Olsen unc-45 lines were generated as recently described Two UAS-RNAi fly lines (construct IDs 9815 and 101311) for the unc-45 RNAi males or virgin females were crossed to Hand-Gal4 flies and incubated at 25°C throughout development. Male and female F-1 progeny were separated and allowed to develop with food changes every third day. The temperature-sensitive Gal4–Gal80 system was used to control timing of RNAi KD  as previously reported w1118 flies crossed with Hand-Gal4 or tub-Gal80-ts; TinCΔ4-Gal4 or w1118 flies crossed with each of the UNC-45 RNAi transgenic lines. Results from female progeny are reported here.For RNAi silencing, Drosophila heart tubes with myosin antibody or fluorescently-labeled phalloidin was carried out using an Apotome Imager Z1 (Zeiss) and an AxioCam MRm (Zeiss) microscope as previously described Semi-intact hearts were prepared as described previously Drosophila UNC-45 antibody as recently described For analysis of UNC-45 and myosin expression, specimens were collected and protein was extracted with Laemmli sample buffer  containing 200 mM β-mercaptoethanol unc-45 KD was carried out using standard genetic techniques as outlined in unc-45 mutant unc-45 RNAi stocks were rescued with transgenic over-expression of UNC-45. Cardiac physiological, structural and biochemical analyses of the rescued hearts were carried out as reported for control and unc-45 KD hearts.Transgenic rescue of the Figure S1RNAi KD of unc-45 with the 24B-Gal4 driver and its impact on myosin expression. (A) Immunoblot analysis of unc-45 expression (top) in 20 h old embryos from control  and unc-45 KD  and 24B-Gal4 > unc45 RNAi-2 (VDRC)) flies. UNC-45 expression was reduced significantly (∼70-80%) in the KD embryos. (B) Myosin content was reduced significantly in the unc-45 KD embryos , however actin content appears to be similar for all groups. Each lane represents the total extracted protein from 20 embryos.(TIF)Click here for additional data file.Figure S2Knock down of unc-45 results in significant reduction in both myosin accumulation and myofibrillar organization. Immunofluorescence micrographs of cardiac tubes from 1 week old flies are shown.  Hearts from controls and  unc-45 KD flies were probed with antibody against muscle myosin and phalloidin respectively as described in the main test. Control cardiac tubes show typical spiral myofibrillar arrangements within the cardiomyocytes . Myofibrillar organization is completely disrupted in unc-45 KD with loss of most myosin-containing myofibrils and significant dilation (C). Remarkably, even with minimal myosin present, myofibrils still form, albeit in a considerably disorganized fashion, as seen by probing with labeled phalloidin, which binds to filamentous actin (D). Myofibrils within cardiomyocytes are shown with blue arrows in A, B and D. KD of unc-45 leads to loss of most myosin-containing myofibrils in cardiac muscle whereas longitudinal ventral muscle myofibrils (white arrow in C) remain unaffected. All images were taken at 25X magnification.(TIF)Click here for additional data file.Figure S3Cardiac defects associated with unc-45 KD in 4-day old adults. (A) Hearts (4-day old) from unc-45 KD flies show prolonged diastolic and systolic intervals compared to control hearts. (B) Diastolic and systolic diameters of the KD hearts were significantly higher compared to age-matched control hearts. (C) Cardiac contractility  of the unc-45 KD hearts was significantly reduced and significant cardiac arrhythmia was observed. Mean values ± SD are shown. Statistical differences between control and unc-45 KD hearts were determined using an unpaired Student's t test (*** =  p<0.001).(TIF)Click here for additional data file.Figure S4Cardiac defects associated with unc-45 KD in third instar larvae. Comparison of cardiac diameter (diastolic and systolic (A) and (B), respectively) and cardiac efficiency ) in control and unc-45 KD hearts from third instar larvae. Both diastolic and systolic cardiac diameters were significantly increased in unc-45 KD larvae hearts. Cardiac performance of unc-45 KD third instar larvae were significantly reduced compared to age matched controls. Statistical differences between control and unc-45 KD hearts were determined using an unpaired Student's t test (* =  p<0.05).(TIF)Click here for additional data file.Figure S5Scheme for transgenic over-expression of unc-45 to rescue defects associated with unc-45 KD. Genetic crosses using multiple balancers were carried out to rescue cardiac phenotypes associated with unc-45 KD. unc-45 RNAi and a cardiac driver  transgenes are inserted in the second chromosome and the transgenic unc-45 gene described in the scheme is inserted in the fourth chromosome. Transgenic unc-45 inserted in the X-chromosome was also used to rescue the cardiac phenotype associated with unc-45 KD.(TIF)Click here for additional data file.Figure S6Transgenic over-expression of unc-45 partially rescues defects associated with unc-45 KD. As for one week-old flies .(TIF)Click here for additional data file.Figure S7Transgenic over-expression of unc-45 partially rescues lethality associated with unc-45 KD. Cardiac-specific KD of unc-45 results in a decrease in mean life span . This reduced lifespan was partially rescued by transgenic over-expression of UNC-45, as only ∼15% of flies are dead in 3 weeks. The average of a total of 250 flies from three experiments was determined for each group.(TIF)Click here for additional data file.Movie S1Control and unc-45 KD adult beating hearts. Representative movies of 1 week old Drosophila hearts; the first clip  shows a typical regularly beating heart. The following clip  shows the irregular beating pattern observed in response to unc-45 KD in the heart. This unc-45 KD heart also exhibits the significant dilation and the reduction in contractility that is typical of these KD hearts.(MOV)Click here for additional data file.Movie S2Control and unc-45 KD white pupae beating hearts. Movie clips of white pupae (young) showing contractions in control hearts  and unc-45 KD hearts . Note increased heart rate in response to unc-45 KD.(MOV)Click here for additional data file.Movie S3Adult beating hearts that had unc-45 KD before or after metamorphosis. Movie clip of 1 week old adult fly hearts where unc-45 KD was carried out either before  or after metamorphosis (following 10s) using the TARGET system and the heart specific TinCΔ4-Gal4 driver.(MOV)Click here for additional data file.Movie S4Control, unc-45 KD and rescued adult beating hearts. Movies of control , unc-45 KD  and unc-45 KD rescued with transgenic over-expression of UNC-45 . The compromised beating pattern and dilation seen in the unc-45 KD are greatly reduced in the rescued heart.(MOV)Click here for additional data file.


Eukaryotic regulatory small RNAs (sRNAs) play significant roles in many fundamental cellular processes. As such, they have emerged as useful biomarkers for diseases and cell differentiation states. sRNA-based biomarkers outperform traditional messenger RNA-based biomarkers by testing fewer targets with greater accuracy and providing earlier detection for disease states. Therefore, expression profiling of sRNAs is fundamentally important to further advance the understanding of biological processes, as well as diagnosis and treatment of diseases. High-throughput sequencing (HTS) is a powerful approach for both sRNA discovery and expression profiling. Here, we discuss the general considerations for sRNA-based HTS profiling methods from RNA preparation to sequencing library construction, with a focus on the causes of systematic error. By examining the enzymatic manipulation steps of sRNA expression profiling, this paper aims to demystify current HTS-based sRNA profiling approaches and to aid researchers in the informed design and interpretation of profiling experiments. RNA in eukaryotic cells can be classified into five categories: ribosomal RNAs (rRNA), transfer RNAs (tRNA), messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and small RNAs (sRNAs). Over 90% of the total RNA molecules present in a cell are rRNA and tRNA, while sRNAs account for ~1% or less. Eukaryotic regulatory sRNAs are a subset of sRNAs ranging in size from ~20 to 30 nt and include microRNAs (miRNAs), small interfering RNAs (siRNAs), and piwi-interacting RNAs (piRNAs). The functions of these regulatory sRNAs are conserved from plants to animals, which imply their involvement in fundamental cellular processes [High-throughput sequencing (HTS) has revolutionized the study of sRNAs by simultaneously accelerating their discovery and revealing their expression patterns. As we have learned from microarray-based sRNA expression profiling , 3, key  In this paper, we discuss preparation of sRNAs for profiling by HTS and enzymatic manipulation upstream of sequencing library preparation. The purpose of enzymatic manipulation is either to improve representation and reduce bias or to specifically focus on subsets of sRNAs based on end modifications. Furthermore, we review the activities of the enzymes directly involved in common HTS library preparation methods and discuss their relative strengths and weaknesses to facilitate choosing suitable protocols and interpretation of the results.Although small in size, eukaryotic regulatory sRNAs are diverse in their sequences, modifications, biogenesis, expression patterns, and functions . sRNAs hmiRNAs are a class of 21 to 24 nt sRNAs in most eukaryotes that regulate gene expression at the transcriptional or posttranscriptional level  and undeMature miRNAs are present in the cytoplasm, mainly within cytosolic P bodies, stress granules, and in association with polyribosomes –12, miRNmiRNAs are now considered to be key regulators of gene expression in higher eukaryotes with estimates that at least 20–30% human protein-coding genes are regulated by miRNAs –21. ReguA second major class of sRNAs is endogenous small interfering RNAs (siRNAs). They are 21 to 23 nt in length and originate from endogenous double-stranded RNAs (dsRNAs) that are either synthesized by RNA-dependent RNA polymerase or that originate from annealed regions within or between endogenous transcripts –26. siRNPiwi-interacting RNAs (piRNAs) are a class of sRNAs that are 26 to 30 nt long and are speculated to be generated from long single-stranded RNA precursors –34. piRNBesides miRNAs, siRNAs, and piRNAs, many other classes of sRNAs exist and novel classes continue to be discovered in many organisms. For example, tasiRNA, natsiRNA, tncRNA, hcRNA, rasiRNA, scnRNA, and 21U-RNA have been identified recently . Their sWith the employment of new technologies, such as HTS, discovering new classes of sRNAs is more feasible. Understanding their biological roles in various aspects of cellular processes and disease states is an important and exciting scientific frontier.Due to their conserved functions in gene regulation, miRNAs have become valuable biomarkers for many diseases and cell differentiation states . For exaDuring their biogenesis, miRNAs can be subjected to various editing events, such as 3′ to 5′ exonucleolytic processing , 49, 3′-Though focused on HTS-based expression profiling, the methods and principles for preparing samples upstream of sequencing library construction discussed here are also applicable to sample preparation for other RNA expression profiling methods. To profile sRNA expression, it is desirable to avoid introducing systematic error from the sample acquisition, RNA extraction, and preparation. It is also critical that these procedures are thoughtfully considered to ensure reproducibility, valid interpretation, and comparative analysis of profiling results.in vivo and in cell culture [Clinical research-related sRNA profiling commonly deals with human samples. Age, sex, race, background comorbidity, anesthesia processes, state of consciousness, and circadian rhythms are potentially relevant to miRNA expression profiling . For exa culture , 63. The culture , 65. AltWhen studying sRNAs from tissues, care must be taken in the tissue processing, which includes tissue procurement, fixation, and embedding. miRNAs appear to be more stable in FFPE tissue than mRNAs, probably due to their small size and reduced likelihood of remaining cross-linked with proteins after proteinase K digestion . Tight csRNAs are often isolated or enriched from extracted total RNA in profiling workflows. Although larger RNAs will eventually be excluded from sRNAs during library preparation, it is critical to maintain the integrity of total RNA to avoid the contamination by degraded large RNAs, especially rRNA. To extract total RNA, routine methods are composed of two steps: deproteinizing RNA in biological samples and precipitation of RNA. Deproteinizing RNA can be achieved by SDS solubilization followed by phenol extraction or TRIzol extraction . It is uEthanol precipitation of sRNAs is commonly used to recover RNAs from ~20 nt to several kilobases in length. When possible, adding a nucleic acid carrier, such as glycogen, linear polyacrylamide, or tRNA, to the sample or prior to the extraction will increase the yield of extraction and precipitation , 69. ComMany column-based RNA isolation kits are commercially available. A key consideration for choosing whether the kit is suitable for sRNA profiling experiments is the retention of sRNA during extraction. Therefore, attention needs to be paid to select appropriate kits to ensure sRNAs retained with high yield during purification. Many of these kits are designed to isolate RNA based on the nucleic acid affinity to silica-based materials in the presence of chaotropic salts, such as guanidinium isothiocyanate, while proteins and other cellular components pass through. Residual contamination of chaotropic salts through purification is possible and can impair downstream enzymatic reactions. Therefore, thorough column washing is advised.After RNA extraction, removal of residual genomic DNA using DNase I is necessary to ensure the purity of total RNAs. It is also highly recommended to check the integrity of total RNA before isolating sRNAs. Total RNA quality and quantity can be determined by gel electrophoresis or on a microfluidics-based technology, such as the Agilent 2100 Bioanalyzer  . The intThough it adds hands-on labor and time, enrichment of sRNAs may be desirable for sRNA library construction because the high abundance of rRNA, tRNA, and mRNA may overwhelm the representation of sRNAs in HTS. sRNAs can be separated from other RNAs using polyacrylamide gel electrophoresis (PAGE). After excising gel pieces in the desired size range, sRNAs can be eluted by crushing and soaking in solution with constant rotation (passive diffusion) or can be more efficiently eluted using an electroelution approach with tubes, such as Mini GeBAflex-tubes . Gel extraction allows for the tightest control of RNA size range to be analyzed in downstream procedures. A variation of PAGE fractionation is the FlashPAGE Fractionator (Life Technologies) which is a minielectrophoresis device that runs small scale polyacrylamide tube gels for isolating RNAs below a threshold length . AnotherDue to their different origins and biogenesis pathways, sRNAs differ from each other in their modifications at the 5′- and 3′-termini . These mMature miRNAs and siRNAs from mammals have a monophosphate at their 5′-ends and 2′-, 3′-hydroxyl groups at their 3′-ends , 7. SecoSome sRNA 5′- or 3′-end modifications are not reactive or have reduced reactivity for enzymatic manipulation in expression profiling protocols. For example, the commonly used T4 RNA ligases can efficiently catalyze the formation of a 3′- to 5′-phophodiester bond between a 3′-hydroxyl group and a 5′-phosphate group –80. ThersRNA 5′-ends can have a 5′-hydroxyl group or contain a mono-, di-, or triphosphate group, or a cap structure. In order to convert sRNAs to have ligatable 5′-monophosphates, a number of enzymes can be utilized, and the choice of enzyme depends on the starting modification and desired enrichment or depletion of different substrates. To capture sRNAs with a 5′-triphosphate, such as secondary siRNAs, the 5′-triphosphate can be removed by alkaline phosphatase to yield a 5′-hydroxyl group. The removal of 5′-phosphate groups to yield a 5′-hydroxyl group has the advantage of preventing RNA self-ligation to form circles and concatemers. This has the net result of improving the yield of properly ligated products when ligating an adapter to the RNA 3′-end . sRNAs wInstead of 5′-phosphorylated DNA adapters, adenylated DNA adapters are widely ligated to RNA 3′-hydroxyl ends since preadenylation allows for the exclusion of ATP in ligation reactions when using T4 RNA ligases. This leads to decreased formation of self-ligated adapter or adapter concatermers , 86. To in vivo. To make these species ligatable, whether naturally occurring or resulting from in vitro manipulation, the adenylyl group at an RNA 5′-end can be removed using 5′-deadenylase in a reaction that liberates AMP to yield 5′-monophosphate ends. 5′-deadenylase is also active on 5′-adenylated DNA ends.It remains to be determined whether there are significant amounts of sRNA species that contain 5′-adenlyated ends TAP hydrolyzes the phosphoric acid anhydride bonds in the triphosphate bridge of the cap structure, releasing the cap nucleoside and generating a 5′-monophosphate terminus on the RNA molecule , 90. RNADue to the presence of 5′-monophosphate groups in sRNAs, such as miRNAs and siRNAs, one can selectively degrade these sRNAs using XRN1, a 5′ to 3′exoribonuclease . DegradaArabadopsis HEN1 is only active on double-stranded sRNAs. HEN1 active on ssRNA in vitro is not yet commercially available [3′-ends of sRNAs can also be differentially modified during biogenesis. piRNAs, for instance, are methylated at the 2′-position of the 3′-terminal ribose. RNAs with a 3′-end 2′-O-methyl group are ligatable by T4 RNA ligases but with significantly decreased efficiency under standard conditions. Ligation reactions using a mutant variant of T4 RNA ligase 2 (T4 Rnl2), T4 RNA ligase 2 truncated (T4 Rnl2tr), at an optimal PEG concentration can significantly improve 3′-adapter ligation efficiency of RNAs with a 2′-O-methyl 3′-end to a level equivalent to that of unmodified RNAs. As a result, their representation in sRNA quantification experiments will be increased . Conversvailable .β-elimination to convert RNAs with a 2′-hydroxyl group at the 3′-end to form unligatable 2′-, 3′-cyclic phosphate ends that are one base shorter  uses two double stranded adapters that contain degenerate 5′- or 3′-end overhangs. These degenerate overhanging sequences allowing the region to anneal to the unknown sRNA ends. After annealing, the nicks between sRNAs and adapters are sealed using T4 RNA ligases. After ligation, the reaction products are reversed transcribed into cDNA by extending the bottom strand of the 3′-adapter and further amplified using primers annealing to both adapter sequences .A second method utilizes polyadenylation. Multiple A residues are added to the 3′-end using Poly(A) polymerase, creating a 3′ polyA tail . One of A third method uses sequential adapter ligations and is widely used for sequencing on the Illumina platform. The method sequentially ligates 3′- and 5′-adapter oligonucleotides directly to the unknown sRNA pools . SimilarUnder standard library construction protocols, sRNAs with 2′-O-methyl modifications at their 3′-ends tend to be underrepresented in HTS-based expression profiling experiments due to the effect of the modification on enzymatic reactions. Both polyadenylation and ligation efficiency of RNAs with a 2′-O-methyl group at the 3′-end are less than that of unmodified 3′-ends . Under oThe reverse transcriptase used for cDNA synthesis is also known to be sensitive to 2′-O-methyl residues in RNA templates , which cIn order to capture sRNAs with a 5′-triphosphate, such as secondary siRNAs, in HTS libraries, the sRNAs can either be enzymatically treated to convert the 5′-triphosphate to 5′-monophosphate as shown in As discussed above, sRNA HTS library construction is achieved through series of enzymatic reactions. T4 RNA ligases are the key enzymes commonly used in all current library construction protocols. Here, we focus on the enzymatic properties of T4 RNA ligases, including T4 Rnl1 and T4 Rnl2, in the context of each library construction protocol.In the hybridization-based ligation method, ligation is dependent on the annealing of the degenerate region of the adapter to RNAs in the sample. The annealing step itself could potentially introduce bias. We detected significant sequence bias in experiments that used degenerate stem-loop RT primers to sequence random oligonucleotide pools. In the experiments, partially double-stranded stem-loop oligos with 3′-overhanging degenerate regions were designed to hybridize with the 3′-end of sRNAs. HTS data from libraries prepared with this approach showed significant bias toward GC sequences in the hybridizing region. Although the study did not involve use of T4 RNA ligase, it is illustrative of the potential bias in sequence composition when degenerate oligos are used for hybridization . StudiesAnother concern in the hybridization-based ligation method arises from the junction substrate specificity of T4 Rnl2. During the annealing process, various types of junctions between RNA and adapter termini can form depending on positioning of the RNA and adapter. Annealing may result in a nick, one or more extra nucleotides flaps at the RNA 5′- or 3′-termini, or gaps. It is known that T4 Rnl2 only promotes the formation of phosphodiester bonds between 3′-hydroxyl ends and 5′-phosphate ends in the nicked arrangement . AnnealeIn the sequential adapter ligation protocol, T4 Rnl1 and T4 Rnl2 are used to attach sequence-specific adapters to the 5′- and 3′-end of sRNAs. Although the preferred substrates of both enzymes are RNAs, T4 Rnl1 and T4 Rnl2 are capable of using 5′-phosphate DNA ends as donors, while T4 Rnl1 is also capable of using a DNA acceptor (3′-hydroxyl) , 113. T44 to form an adenylated RNA intermediate and thus T4 Rnl2tr requires preadenylated donor molecules for ligation [T4 Rnl2tr, a C-terminal truncated T4 Rnl2, has desirable features for use in sRNA library construction. The C-terminal domain of T4 Rnl2 is implicated in transferring AMP from ligase to 5′-POligation . By usinligation . In ligaligation , 86, 115ligation , 106. ThA recent study using a pool of synthetic miRNAs showed that the inconsistencies in miRNA quantitation in HTS are mainly derived from the adapter ligation steps . The biacDNA synthesis by reverse transcriptase (RT) is a common step in all RNA HTS library construction methods. Both fidelity and the ability of RT to synthesize full-length cDNA can potentially impact sRNA profiling by HTS.In terms of base misincorporation rates, the fidelity of RTs is lower than that of modern proofreading DNA-dependent DNA polymerases used in HTS library construction. While potentially problematic for sRNA variant discovery, we would argue that the contribution of base misincorporation to systematic error in sRNA profiling by HTS is insignificant. The base misincorporation rate of AMV and MLV RTs are ~1/17,000 and ~1/30,000, respectively, as reviewed in . Based oInsertion and deletion errors by RT are less well characterized than misincorporations, and their impact on sRNA profiling by HTS remains to be determined. Similarly, further elucidation of the causes of RT mutational hotspots , if theyUntemplated 3′-end nucleotide addition by RT is disadvantageous for protocols synthesizing cDNAs prior to ligation steps. This activity might be problematic for experiments where the precise determination of the sRNA 5′-end is required as discussed in RT primer extension of a panel of 5′- and 3′-ligated synthetic miRNAs showed no differences in the yields of cDNA synthesized . These rThe relatively low number of miRNAs per genome (1520 human miRNAs in miRBase version 18)  and theiConsidering the observed bias originating from T4 RNA ligases, introducing barcodes during or prior to any of the ligation steps seems potentially problematic from the viewpoint of sRNA profiling. The different barcode sequences can influence the RNA and adapter cofold structures, likely resulting in barcode-dependent changes in ligation efficiency of sRNAs in the sample. Similarly, changing the adapter sequences can also be expected to change ligation efficiency for specific sRNAs. The net effect of these changes could confound the interpretation of expression profiling results.Introducing barcodes in the reverse transcription or PCR steps seems less likely to cause biases in estimation of sRNA levels. However, this approach is not without caveats. It is known, for instance, that multiple-template PCR amplification can result in a sequence-dependent amplification bias due to sequence differences . CarefulFrom the perspective of RNA ligase-dependent sRNA HTS library construction for expression profiling, it seems clear that library construction protocols, including ligation enzyme reaction conditions and adapter sequences, warrant careful consideration for the interpretation of results. When the libraries are prepared with the same protocol, comparisons of individual miRNA levels between libraries are likely valid and reproducible. Quantification of different sRNAs within a library or quantitation of specific sRNAs between samples prepared with different protocols may be influenced by the protocols themselves. The inclusion of spike-in external standards and careful secondary validation are critical to accurate interpretation of profiling results.Validating expression profiles using alternative methods is essential due to the limitations and systematic error that may exist in any profiling method. Quantitative PCR, Northern Blot hybridizations, and microarrays are widely used methods for sRNA expression profiling –132. TheIn situ hybridization is also used for sRNA profiling validation. This approach provides the advantages of revealing expression level and localization of sRNA simultaneously but can analyze only a limited number of known targets in a single experiment. This approach has been a useful and powerful tool to provide more insights and focused analyses of individual and limited sets of sRNAs [of sRNAs , 134.Other emerging alternative sRNA profiling methods based on electrochemical, bioluminescence, raman signals, and surface plasmon resonance are well discussed in a recent review .Realizing the biases discussed here for current HTS-based profiling, the successful development of an amplification free, direct RNA sequencing platform is particularly attractive to obtain a comprehensive and bias-free profiles of the transcriptome , provideProfiling techniques that provide sensitive detection with large dynamic range but do not require the modification of sRNAs seem ideal. As we look toward the future, new technologies such as nanopores may be able to satisfy some of these criteria. For example, a recent report demonstrated proof of principle for nanopore detection of sRNAs using specific hybridization probes and the viral siRNA binding protein p19 to analyze specific miRNA in a total RNA sample . While tThis paper has discussed many of the sources of inaccuracy and bias that can arise in expression profiling of sRNAs. We focused on the implications of enzymatic manipulation of sRNAs using HTS library construction as an example. Although there are numerous steps where systematic error can be introduced in these workflows, HTS remains the most powerful current method for expression profiling and sRNA discovery. Enzymatic manipulation of nucleic acids in expression profiling will continue to be important, even as hardware platforms change. Thus, it is important that experimental design and interpretation of expression profiling experiments thoughtfully consider the capabilities of enzymes used as tools in order to produce high-quality data sets and to generate valid comparisons between them.


Single-cell sampling with RNA-seq analysis plays an important role in reference laboratory; cytogenomic diagnosis for specimens on glass-slides or rare cells in circulating blood for tumor and genetic diseases; measurement of sensitivity and specificity in tumor-tissue genomic analysis with mixed-cells; mechanism analysis of differentiation and proliferation of cancer stem cell for academic purpose. Our single- cell RNA-seq technique shows that fragments were 250–450 bp after fragmentation, amplification, and adapter addition. There were 11.6 million reads mapped in raw sequencing reads (19.6 million). The numbers of mapped genes, mapped transcripts, and mapped exons were 31,332, 41,210, and 85,786, respectively. All QC results demonstrated that RNA-seq techniques could be used for single-cell genomic performance. Analysis of the mapped genes showed that the number of genes mapped by RNA-seq (6767 genes) was much higher than that of differential display (288 libraries) among similar specimens which we have developed and published. The single-cell RNA-seq can detect gene splicing using different subtype TGF-beta analysis. The results from using Q-rtPCR tests demonstrated that sensitivity is 76% and specificity is 55% from single-cell RNA-seq technique with some gene expression missing (2/8 genes). However, it will be feasible to use RNA-seq techniques to contribute to genomic medicine at single-cell level. Clinical specimens are tremendously different from biological specimens in that the former contain mixed cells while the latter are mostly composed of pure cells. A mixed cell population in clinical samples can mask real results of genomic data, resulting in an inaccuracy of routine clinical genomic analysis and clinical genomic diagnosis. However, genomic medicine requires precise genomic profiling of clinical specimens to work for a clinical genomic diagnosis and to design personalized therapy for genetic and cancerous diseases. Like most routine diagnosis techniques , 2, clinTILs, one type of the cells located in tumor tissue, are responsible for immune surveillance to tumor cells . If the μL DNA digestion buffer with DNase I (Sigma). Two  μL DNA digestion solution was added to a cocktail mixture containing 1 μL dNTP, 1 μL 50 mM 3′ anchor primer containing [5′-CTCTAAGCTT(T)11-3′], 2 μL MgCl2, 1 μL 10x buffer, 0.25 μL RNasin, 0.25 μL AMV reverse transcriptase, and 4.5 μL sterile ddH2O . First-strand synthesis was performed at 25°C 10 min, 42°C 1 hour, and 95°C 5 min. The cDNA was amplified by PCR with four arbitrary 5′ primers and oligo-T primers as in μL volume using AmpliTaq Gold from Perkin Elmer, USA. TIL CD8 cell library was stored at −80°C for further study. RNA of PBMN T-cell control  was isolated, and a cDNA library was generated similar to TIL.Single CD8 cells obtained from TIL of liver cancers were isolated, and a cDNA library was generated as previously reported . BrieflySequencing Library. The protocol is the same as shown in Illumina TruSeq RNA sampling process [ process . BrieflyAlignment of Sequenced Reads. The alignments were performed using the tool Galaxy. Galaxy was professionally developed for short oligonucleotide analysis, allowing up to 2 mismatches with the references. Sequenced reads were aligned to human transcript reference sequences from the human hg19 for the expression analysis at gene/transcript levels by Tophat and differential analysis by Cufflinks and Cuffdiff in Galaxy platform.Evaluation of Data. To test the feasibility of sequencing, the correlation of gene expression between genes of RNA-seq whose data was from gene expression level as RPKM (reads per kilobase of transcript per million mapped reads) and single-cell differential display genomics (which we have published in 2009) [in 2009)  was usedhttp://linus.nci.nih.gov/BRB-ArrayTools.html) [To analyze the data of RNA-seq, the mapped genes were used to research the fold change by RPKM. Briefly, RPKM from PBMN and TIL were input into BRB ArrayTools (ls.html) . We seleμL PCR reaction mixture, totaling at 50 uL containing 25 uL 2x SYBR Green (BioRad), 500 nM for each primer, RNA extracts, and iScript reverse transcriptase 1 uL. According to the primer conditions and manufacturer's recommendations, one step real-time PCR was 10 min at 50°C and 5 min at 95°C, followed by 45 cycles of denaturation for 10 s at 95°C and annealing/extension for 30 s at 55°C. The SYBR fluorescent signals were quantitatively analyzed as previously reported [The Q-rtPCR assay was performed in triplicate for each gene with the 25 reported .After the library of DNA was fragmented with downstream end-repair process and a single “A” base addition, the fragments were ligated to adapters following Illumina TruSeq kit protocol and sequencing libraries were enriched by PCR and 2100 bioanalyzer as shown in http://dx.doi.org/10.1155/2013/724124.After the RNA-seq experiment harvested 19.6 million sequencing reads, 11.6 million aligned reads were achieved. All data analysis of the RAN-seq was performed in Galaxy local system as shown in After mapping the genes, mapped transcripts or mapped exons were mined, and mapped genes were applied for data analysis. The results of the gene expression Boxplot are given in After SAM analysis, a total of 6767 genes were filtered from SAM RNA-seq, and results were compared to 288 libraries from differential display. Eight silence genes were mined in single-cell differential display shown in In our previous experiment, TGF-beta had higher expression in TIL as measured by Q-rtPCR and differential display. Here, all family members of TGF-beta  in TIL were expressed lower than those of T-cell in PBMN by single-cell RNA-seq as shown in A major task of clinical genomics is to study the levels of mRNA/protein expression and to discover functional SNPs related to a disease specific to the patient. Traditional approaches to identify and quantify genomic expression include mRNA microarrays , express5–1.5 ×106 molecules based on different cell types) [As we all know, the quantity of whole genome DNA is 6.6 pg with two copies in single cell . Becausel types) , unstabll types) . To dateResults of the quality of RNA-seq demonstrated that most fragments ligated to adapters were 250–450 bp indicating an intact mRNA at single-cell level. Among the 19.6 million sequencing reads, 11.6 million reads were mapped. The numbers of mapped genes, mapped transcripts, and mapped exons were 31,332, 41,210, and 85,786. The QC results indicated that RNA-seq techniques can be used for single-cell genomic performance. After the mapped genes were applied for data analysis, the results of gene expression described with both boxplot and scatter-plot did not show bias. Unexpectedly, a total of 6767 genes were discovered in RNA-seq by SAM mining. The results suggest that RNA-seq is more powerful than differential display (only mining 288 libraries). The Q-rtPCR test demonstrated that sensitivity and specificity from RNA-seq technique were 76% and 55%, respectively. As most single-cell genomic techniques, gene missing rates are still higher (2/8 genes) including internal control analysis (2/6 genes) as shown in Supplemental Table 6. Encouragingly, RNA-seq at single-cell level is also able to uncover gene's splicing in mRNA expression as routine RNA-seq .With this new RNA-seq technique, it would give researchers a new tool to study the single-cell genomics techniques. Results of RNA-seq including quality control, mapped reads, and the discovery rate demonstrated that RNA-seq techniques could be used for single-cell genomic analysis. The Q-rtPCR test demonstrated that sensitivity and specificity from RNA-seq techniques are lower than those from differential display with missing gene expression. This result demonstrated that RNA-seq still requires more time to be modified. However, it will be feasible to use RNA-seq techniques to contribute to genomic medicine at single-cell level.Table S1: FPKM table.Table S2: Gene expression table.Table S3: Transcript expression table.Table S4: Splicing expression table.Table S5: Gene analysis table.Table S6: Internal control gene expression table.Click here for additional data file.


Further, the analysis of a biological specimen's associated microbiome can also be performed using RNA-seq data and this application is gaining interest in the scientific community. There are many existing bioinformatics tools designed for analysis and visualization of transcriptome data. Despite the availability of an array of next generation sequencing (NGS) analysis tools, the analysis of RNA-seq data sets poses a challenge for many biomedical researchers who are not familiar with command-line tools. Here we present RNA CoMPASS, a comprehensive RNA-seq analysis pipeline for the simultaneous analysis of transcriptomes and metatranscriptomes from diverse biological specimens. RNA CoMPASS leverages existing tools and parallel computing technology to facilitate the analysis of even very large datasets. RNA CoMPASS has a web-based graphical user interface with intrinsic queuing to control a distributed computational pipeline. RNA CoMPASS was evaluated by analyzing RNA-seq data sets from 45 B-cell samples. Twenty-two of these samples were derived from lymphoblastoid cell lines (LCLs) generated by the infection of naïve B-cells with the Epstein Barr virus (EBV), while another 23 samples were derived from Burkitt's lymphomas (BL), some of which arose in part through infection with EBV. Appropriately, RNA CoMPASS identified EBV in all LCLs and in a fraction of the BLs. Cluster analysis of the human transcriptome component of the RNA CoMPASS output clearly separated the BLs  from the LCLs (which have a blast-like phenotype) with evidence of activated MYC signaling and lower interferon and NF-kB signaling in the BLs. Together, this analysis illustrates the utility of RNA CoMPASS in the simultaneous analysis of transcriptome and metatranscriptome data. RNA CoMPASS is freely available at  Fusobacterium and colorectal carcinoma was made using two different NGS approaches Through its capacity to delve deeply into the genetic composition of a biological specimen, next generation sequencing (NGS) technology presents an unprecedented approach to pathogen discovery in the context of human disease. This unbiased approach to identify undiscovered human disease causing pathogens has already shown promise, resulting in the discovery of a novel Merkel cell polyomavirus in Merkel cell carcinoma While current sequence-based computational subtraction pipelines are used solely for pathogen discovery, RNA CoMPASS, takes advantage of the richness of RNA-seq data to provide host transcript expression data in addition to pathogen analysis. This concept, recently coined “dual RNA-seq” by Westermann and colleagues RNA-seq data sets from 22 Human B-Cell samples (lymphoblastoid cell lines [LCLs]) immortalized with Epstein-Barr Virus (EBV) were downloaded from the NCBI Sequence Read Archive (SRA010302). Samples were sequenced using an Illumina Genome Analyzer II machine running single end 50 base sequencing reactions. Similarly, 22 Human Burkitt's Lymphoma (BL) samples were obtained from the NCBI Sequence Read Archive (SRA048058). Samples were sequenced using an Illumina Genome Analyzer II machine running paired end 107 and 102 base sequencing reactions. The Akata RNA-seq data set was generated previously in our lab (SRA047981) www.novocraft.com)  with a reference genome ), splice junctions  is a graphical user interface (GUI) based parallel computation pipeline for the analysis of both exogenous and human sequences from RNA-seq data. Several open source programs and a single commercial program are utilized in this automated pipeline. For the deduplication steps, an in-house de-duplication algorithm is used. Alignments to the reference genome are carried out using Novoalign V2.07.18 (P<0.05 following the Benjamini-Hochberg correction for multiple testing. The fitted log(CPM) values for the subset of genes that were differentially expressed in the LCL samples relative to the BL samples were then clustered using the Euclidean distance and complete linkage algorithm to detect groups of co-expressed genes.Human transcript counts were imported into the R software environment and analyzed using the edgeR package http://www.novocraft.com/) . Any host genome can be uploaded to RNA CoMPASS. In our case, we used the human reference genome, hg19 (UCSC), plus splice junctions . To further reduce the computational burden incurred by BLASTing these unmapped host reads, RNA CoMPASS offers an optional stage prior to NT database BLASTing where the user can BLAST against a host transcript database. Because host transcript databases are much smaller than the NT database, host reads not aligned by Novoalign can be filtered out at lower computational cost than would otherwise be incurred by BLASTing these reads against the NT database.Exogenous sequence analysis proceeds concurrently with the endogenous analysis . UtiliziAfter BLASTing against the NT database, taxonomic analysis is performed by importing the BLAST results into MEGAN In RNA CoMPASS, we have implemented both the Java Parallel Processing Framework (JPPF) API and Portable Batch System (PBS) API in order to deploy it on either a small local cluster or a grid system managed by PBS submission. Our testing of RNA CoMPASS in both environments (data not shown for grid system) showed that our pipeline could efficiently analyze RNA-seq data sets achieving a significant speedup over analysis on a single machine. This will allow other investigators to use RNA CoMPASS on whichever type of computational environment they have access to. In our case, we employed RNA CoMPASS on a local 4-node cluster environment (Intel Xeon Mac Pros with 64–96 GB RAM).To evaluate the performance of RNA CoMPASS on a cluster environment versus a single node environment, we benchmarked 6 RNA-seq data sets with incrementally varied file sizes on both a single machine and on a local cluster with 4 nodes. The 6 files used for this analysis were extracted from a previously generated RNA-seq data set from a BL cell line (1 sequence pair from the Akata RNA-seq data set) To test the utility of RNA CoMPASS to identify pathogens within biological specimens we used RNA-seq data sets from two distinct B-cell types, lymphoblastoid cell lines (LCLs) and Burkitt's lymphoma (BL) samples. LCLs are not tumor cells but have instead been immortalized by infection with EBV. In contrast, the Burkitt's lymphoma cells lines are tumor cell lines, some of which underwent tumorigenesis in part through natural infection with EBV. Notably, however, although some Burkitt's lymphoma cell lines are infected with EBV, the EBV gene expression pattern and the cell phenotype of Burkitt's lymphomas and LCLs are distinct.Single-end RNA-seq data sets from 45 B-cell lines  were analyzed using RNA CoMPASS . Most saAs expected, EBV gene expression in LCLs is generally more robust and shows the expression profile expected in this cell type with all the latent proteins including EBNA 1,2, and 3 and LMP 1 and 2 being expressed . In contThe host transcriptome analysis component of RNA CoMPASS generates gene expression output files that can be used for cluster and pathway analysis. Gene expression output from RNA CoMPASS analysis of the 22 LCL and 23 BL samples was subjected to hierarchical clustering and differential gene expression analysis . FurtherTo investigate differences in LCLs compared to BLs, Ingenuity Pathway Analysis software (IPA: Ingenuity Systems) was used to assist in the analysis of signaling pathways and molecular functions associated with the differentially expressed cellular genes. Upstream regulator analysis within IPA predicted activation of MYC (z-score: 3.375), MYCN (z-score: 2.813), MAPK9 (z-score: 2.414), and MAPK1 (z-score: 2.138) pathways with an inhibition of Interferon alpha (z-score: −2.916), interferon gamma (z-score: −2.788), NF-kB (z-score: −2.746), interferon alpha-2 (z-score: −2.723), and interferon lambda (z-score: −2.000) pathways in BL relative to LCL samples  and S3. RNA CoMPASS is designed to take advantage of several open source programs in order to streamline and accelerate RNA-seq data analysis. RNA CoMPASS helps the researcher to manage the computational burden of processing large sets of RNA-Seq data by parallelizing the most compute intensive steps of the process and automatically managing files through each step of the pipeline. The simultaneous analysis of the host transcriptome along with the discovery of pathogens allows investigators to not only detect pathogens but also study the relationship between the pathogen and host transcription.In RNA CoMPASS, we have implemented both the Java Parallel Processing Framework (JPPF) API and Portable Batch System (PBS) API in order to deploy it on either a small local cluster or a grid system managed by PBS submission. Our testing of RNA CoMPASS in both environments showed that our pipeline could efficiently analyze RNA-seq data sets achieving a significant speedup over analysis on a single machine. This will allow other investigators to use RNA CoMPASS on whichever type of computational environment they have access to. In our case, we employed RNA CoMPASS on a local 4-node cluster environment (Intel Xeon Mac Pros with 64-96GB RAM) which achieves a speedup approaching the theoretical limit of 4 by splitting the computational tasks over 4 machines as the file size increases. This speedup of a 4 node cluster serves as a proof of principle that an even greater speedup could be obtained using a significant computational cluster involving hundreds of nodes. A recently published study Though the BLASTing step of RNA CoMPASS incurs moderate limits on the size of input file that can be processed , it allows for a more comprehensive analysis. In previous work, we would that sampling 10 million reads from an RNA sequencing experiment is likely to be well beyond the number needed to detect meaningful levels of exogenous agents We used LCLs and BL samples to evaluate the pathogen and host transcriptome analysis arms of RNA CoMPASS because of their differences in phenotypes. The LCLs were generated by infecting human B-cells with EBV, which typically display an activated B-cell like phenotype  and BART transcripts). The BL samples typically display a germinal center-like phenotype (type I latency – expressing EBNA1 and BART transcripts). The entire sequence file for all samples was used as input for RNA CoMPASS. Although the BL samples were sequenced using a paired-end approach, only one of the reads from each pair was analyzed in order to remain consistent among all samples and because a single-end read should provide sufficient evidence for pathogen discovery.RNA CoMPASS discovered a significantly larger proportion of EBV (Human Herpesvirus 4) reads within the LCLs as compared to the BLs. This is an anticipated result, which validates the usage of RNA CoMPASS to interrogate genetic material of exogenous origin.One of the most highly active pathways within BLs is the MYC pathway. In our study, the MYC and MYCN pathways were predicted to be the top two activated pathways in BLs relative to LCLs according to IPA's upstream regulator analysis. Several MYC targets have been reported in the literature Transcriptome analysis has shown that the MYC signature is the hallmark signaling difference between Burkitt's lymphomas and diffuse large B-cell lymphomas with: upregulation of MYC-target genes and downregulation of genes involved in the NF-kB and interferon responses On the other hand, the most highly inhibited pathways within BLs compared to LCLs were the interferon response pathway and the NF-kB pathway. The NF-kB pathway has been shown to play a vital role in EBV's ability to transform naïve B-cells as the EBV transforming latency protein, LMP1 continuously activates NF-kB A few other noteworthy genes that were observed as being differentially expressed include TCF3 and TOP2A, both of which have increased expression in BLs relative to LCLs. In a recent study using RNA-seq with RNA interference screening of BLs, Schmitz et al was able to identify mutations affecting the transcription factor TCF3 in vitro and in vivoThe other molecule, TOP2A has been shown to determine anthracycline-based drug (e.g. doxorubicin) response http://rnacompass.sourceforge.net. Installation guidelines, supporting documentation, along with example data are available from the sourceforge repository. The most up to date source code is available from the sourceforge site; the version of the source code at the time of publication is included in In summary, our results demonstrate the utility of RNA CoMPASS in analyzing large sequence datasets for the discovery of pathogens and host transcriptome analysis. The use of this pipeline is expected to enable more researchers to enter the filed of RNA Sequencing and to yield novel associations between pathogens and human diseases with important medical implications. This study shows the disparate expression profiles between Lymphoblastoid cell lines and the Burkitt's lymphoma samples thereby exhibiting the ability of RNA CoMPASS to analyze endogenous sequencing. RNA CoMPASS is publically available under the GPL: We are planning to implement the Circos plot capability for discovered pathogens as well as clustering analysis for host gene expression in later versions of RNA CoMPASS. These improvements will further streamline and complement the analysis of RNA-seq data in the discovery and analysis of pathogens associated with malignancies. In addition, we are investigating ways to further improve the speedup of the pipeline.Figure S1Performance of RNA CoMPASS based on individual tasks. The six Akata RNA-seq data set files used previously were benchmarked on completion of individual tasks and represented in the graphs. Runs on a single node are represented using blue columns while runs on a 4-node cluster are represented using red columns. The green line represents speedup time between the single node and 4-node environment. Note in particular that speedup of the BLAST portion of RNA CoMPASS and overall speedup approaches the theoretical limit of 4 as the data size is increased.(TIF)Click here for additional data file.Figure S2Predicted top activated upstream pathway of top 250 differentially expressed genes.(TIF)Click here for additional data file.Figure S3Predicted top inhibited upstream pathway of top 250 differentially expressed genes.(TIF)Click here for additional data file.Table S1Sample list.(XLS)Click here for additional data file.Table S2Top 250 differentially expressed genes between lymphoblastoid cell line and Burkitt's lymphoma samples.(XLS)Click here for additional data file.Table S3All differentially expressed genes between lymphoblastoid cell line and Burkitt's lymphoma samples.(XLS)Click here for additional data file.Software S1Source code for RNA CoMPASS.(TXT)Click here for additional data file.


The following steps of the microdissection workflow: cryosectioning, staining, dehydration and harvesting of microdissected cells have been carefully considered and designed to ensure cell capture efficiency without compromising RNA integrity.Laser-capture microdissection (LCM) that enables the isolation of specific cell populations from complex tissues under morphological control is increasingly used for subsequent gene expression studies in cell biology by methods such as real-time quantitative PCR (qPCR), microarrays and most recently by RNA-sequencing. Challenges are i) to select precisely and efficiently cells of interest and ii) to maintain RNA integrity. The mammary gland which is a complex and heterogeneous tissue, consists of multiple cell types, changing in relative proportion during its development and thus hampering gene expression profiling comparison on whole tissue between physiological stages. During lactation, mammary epithelial cells (MEC) are predominant. However several other cell types, including myoepithelial (MMC) and immune cells are present, making it difficult to precisely determine the specificity of gene expression to the cell type of origin. In this work, an optimized reliable procedure for producing RNA from alveolar epithelial cells isolated from frozen histological sections of lactating goat, sheep and cow mammary glands using an infrared-laser based Arcturus Veritas LCM  and capturing microdissected cells during less than 2 hours before RNA extraction. In addition, particular attention was paid to animal preparation before biopsies or slaughtering (milking) and freezing of tissue blocks which were embedded in a cryoprotective compound before being immersed in isopentane. The amount of RNA thus obtained from ca.150 to 250 acini  ranges between 5 to 10 ng. RNA integrity number (RIN) was ca. 8.0 and selectivity of this LCM protocol was demonstrated through qPCR analyses for several alveolar cell specific genes, including LALBA  and CSN1S2 (αs2-casein), as well as Krt14 (cytokeratin 14), CD3e and CD68 which are specific markers of MMC, lymphocytes and macrophages, respectively.The best results were obtained when staining 8 μm-thick sections with Cresyl violetRNAs isolated from MEC in this manner were of very good quality for subsequent linear amplification, thus making it possible to establish a referential gene expression profile of the healthy MEC, a useful platform for tumor biomarker discovery. One of the main challenges biologists currently face is overcoming the problem of tissue heterogeneity to further understand organ function. It is crucial to distinguish which cell populations produce specific molecules or to get relevant expression profiles reflecting in vivo status.Milk is synthesized in mammary gland during lactation and though this process has been thoroughly studied, we still do not know precisely what mechanisms are involved in the intracellular transport and secretion of milk components, including supra-molecular structures, such as casein micelles ,2 which Mammary parenchyma consists of secretory alveoli organized into lobules and interconnected by a system of branching ducts separated from adipocytes by multiple layers of fibroblastic connective tissue. In the duct and alveoli, the mammary epithelium is organized into two layers, a basal layer of myoepithelial cells (MMC) and a luminal layer of MEC that secretes milk . The extet al. [Advances in molecular biology have provided new tools, including gene expression profiling, to analyze mechanisms controlling mammary gland development and differentiation ,7 and reet al. . On the et al. -11, but et al. ,13. Analet al. ,15.Therefore, to accurately and reliably follow molecular changes occurring in MEC for comparison purposes between physiologically different stages and genetically or environmentally perturbed systems, it is necessary to isolate MEC preserving biomolecule (RNA and proteins) integrity.Different techniques, such as immunomagnetic separation -19, cellin vitro. In addition, it is well-established that MEC in culture are subjected to dedifferentiation [Another means to obtain MEC homogeneous populations is from cell culture. However, one major obstacle to molecular biological studies of MEC is the lack of established cell lines that secrete, or can be induced to secrete, fat globules and milk proteins . While cntiation .et al. [Laser Capture Microdissection (LCM), first described by Emmert-Buck et al.  is now wNevertheless, LCM is an appealing technique, but it introduces additional methodological hurdles, including tissue handling  and maintenance of molecular integrity. The success of a microdissection experiment first depends upon the ability to distinguish cell types of interest from their morphological features. Immunological labelling may be required and used to assist in the identification of cells. In other words, if gene expression experiments are targeted, the challenge is to design a global protocol ensuring acceptable tissue morphology to facilitate isolation of cells while preserving accessibility and integrity of RNA, keeping in mind that this is critically tissue-dependent.Successful application of LCM in transcriptomic analyses relies upon three critical factors: good tissue morphology, capture efficiency, and maintenance of RNA molecular integrity. Effective balancing of these three factors is required to recognize regions and obtain reliable transcriptomic results. Since ruminant mammary gland is one of the richest tissues in RNAse activity, classical protocols require accommodation to preserve RNA from RNase (endogenous and exogenous) and keep it intact in captured cells. This study was carried out to address these issues with the aim of developing a convenient and reproducible protocol to isolate MECs from ruminants  lactating mammary gland, preserving tissue morphology and RNA integrity, to develop a comprehensive overview of the genome expressed in MECs in their physiological environment.Given that recent studies -38 repor® (TissuTek™) in a cryomold of 1 cm3 (Bayer™) and immediately immersed in liquid nitrogen or in SnapFrost™ system  containing cold isopentane at -80°C. Alternatively, some pieces were directly introduced in empty 1.5 ml cryotubes and immediately frozen in the same way (liquid nitrogen or SnapFrost™ system). Samples were stored at -80°C until further processing. The time delay between slaughtering and tissue freezing was less than 20 minutes.Surgical and experimental procedures were performed in compliance with the policies of INRA's Animal Care Committee. Mammary tissue was sampled from 5 goats, 2 ewes and 1 cow euthanized under safe and painless conditions, at the middle of lactation after milking and slaughtering. To preserve morphology and RNA quality we applied two different methods of freezing (liquid nitrogen or cold isopentane) immediately after collection with and without embedding medium as follows: the collected tissue was washed in cold PBS solution, 3-5 mm pieces of tissue were cut 3 and embedded in OCT®) and rinsed in three baths of distilled water before a final bath in 70% ethanol. To test whether the effect of slide temperature plays a key role in detachment of MEC from glass slides during the laser-capture process, pre-cleaned slides were chilled (on ice or at 4°C) or not (room temperature) before transfer. Manufacturers' and published protocols recommend cutting 5 to 12 μm section thicknesses. Tissue sections were 8 μm thick, a compromise to ensure an optimal RNA yield preserving morphology as well as dehydration and laser-capture process efficiency.Frozen tissue blocks were mounted on the cryostat stage  set at -20°C. Before transfer, the working environment was treated to be RNAse free and glass slides  were pre-cleaned with RNAse Zap™  or Cresyl violet® . Different protocols for dehydration and staining of frozen mammary sections were compared  after section transfer, two different methods of cold storage were tested: after cutting, the slides were immersed in cold 75% ethanol and placed at -20°C or put directly into a tube containing desiccant and stored at -80°C. To avoid RNA degradation, each step of the slide preparation process was performed as quickly as possible. Water was RNAse free. Bottles of absolute ethanol  and M-Xylene, anhydrous, >99%  were opened just before use to dehydrate a maximum number of 8 slices a day to ensure proper dehydration. Sections were stained using Histogeneed Table . They we® staining. Two chemical protectors were used: RNA later®  or RCL2® , a new fixative which preserves morphology and nucleic acid integrity. In protocols N°3 to 5, 100 μl of RCL2® or RNA later® were dropped on the tissue section just before staining, to react for 30 s and removed by tapping the slide on an absorbent paper. RNase out  or RNAsin (Promega) were prepared  and added on slice for 15 s during staining step.To preserve the quality of RNA during staining, without ruining the morphology, we tried to add RNA protectors  used commonly to block RNAse activity, before HistoGene®). Capture, which is the gentlest technique and thus maximizing biomolecules integrity, was performed under 40× or 100× magnifications using CapSure LCM macrocaps . IR Laser setting was chosen to maximize the size of the laser spot in the middle of alveoli  without contaminating the sample with non-target-tissue (MMC or interlobular stroma). Laser setting ranged between 75 to 90 mW in power, 1,300 to 3,500 μsec in duration, and 200 mV in intensity. Efficiency of microdissection was evaluated by examining the cap after capture and the tissue section remaining on the slide before and after lifting off the cap: if necessary, the non target tissue can be removed directly on the cap by lower power UV laser (2-5 mW).The LCM process was carried out using the Veritas Microdissection Arcturus system and software (Applied Biosystems2 (around 150 to 200 acini).The critical time limit for capture was estimated by examining RNA integrity and was evaluated from 30 minutes to 2 hours. The corresponding target area was between 300,000 and 600,000 μm® RNA Isolation Kit  according to the manufacturer's instruction protocol, including on-column RNase-free DNase I treatment . CapSure macrocaps with captured cells were inserted into RNase-free 500 μl microcentrifuge tube containing 25 μl of extraction buffer (XB). The tubes were inverted to allow the reaction between the buffer and the surface of the cap. RNAs were extracted from scraped sections (tissue remaining on the slide after capture) by pipetting 50 μl of XB buffer onto the remaining tissue on the glass slide and gently scraped off and transferred in RNase-free 500 μl microcentrifuge tube. RNAs from cap and section scrapes were eluted respectively with 15 μl and 30 μl of elution buffer (EB). To assess RNA quality of tissue before manipulation, one cryo-section of mammary tissue was immediately treated to extract RNA using the same protocol as that for section scrapes after LCM.Total RNA was extracted from captured cells using the PicoPurePurity, concentration and integrity of total RNA isolated in this manner were assessed using two independent techniques. RNA purity was evaluated by absorbance readings (Ratio A260/A230 and A260/A280) using the NanoDrop ND-1000 spectrophotometer . The fluorimetric method and micro-capillary electrophoresis device developed by Agilent Technologies was chosen to determine RNA concentration and quality with RNA 6000 pico LabChip Kit in the Agilent Bioanalyzer 2100 system. Quality was evaluated using the RNA Integrity Number (RIN) value introduced by Agilent .20 and random primers  using Superscript III reverse transcriptase  according to manufacturer's instructions. Then, 1 μl of RNase H  was added and incubated 20 min at 37°C to remove RNA. The obtained cDNA was stored at -20°C before qPCR.First-strand cDNA was synthesized from 5-10 ng total RNA primed with oligo(dT)CSN1S2 and LALBA transcripts, two specific markers of MEC, were quantified using qPCR (SYBR Green chemistry). Two internal control genes, S24 ribosomal protein (RPS24) and cyclophylin (PPIA) were quantified for accurate normalization of data [To estimate MEC enrichment obtained after LCM,  of data .Krt14), lymphocytes (CD3e) and macrophages (CD68). We also quantified transcripts from Fatty Acid Synthase (FASN) which is expressed in several cell types including MEC and adipocytes.Primers used were previously described ,40 and q®). Primers were designed and purchased from Eurofins Genomics (France) to amplify goat, sheep and cow genes (Table ®). First, primers efficiency was validated with a standard curve of four serial dilution points of a scraped section cDNA pool , and a no template control (NTC). qPCR amplification mixture (20 μL) contained 5 μL single strand cDNA template diluted 4 times after reverse-transcription, 10 μL 2× Power SYBR Green PCR Master Mix buffer (Applied Biosystems®) and 1.2 μL forward and reverse primers (5 μM) to reach a final primer concentration of 300 nM. After optimization of qPCR systems (efficiency -3.32 to -3.4), we used the ΔΔCt method and RQ Manager Software , as well as in the relative expression software tool , to compare expression of each gene between captured cells and its scraped tissue, following the MIQE guidelines [Comparing the structural organization of encoding genes across species  and mRNA sequences at exon-exon junctions, we identified highly conserved regions on which primer pairs were designed, using Primer Express Software, version 2.0 (Applied Biosystemsidelines .RPS24 and PPIA) was evaluated with GeNorm Visual Basic application for Microsoft Excel as described by [Reliability of reference genes , based on Pair Wise Fixed Reallocation Randomized Test© [The relative expression for each gene of interest between caps versus scraped tissues was tested for significance by a randomized test implemented in the relative expression software tool  on cell isolation and RNA yield and integrity.ca. 150 slides of tissue sections were cut from 8 mammary glands taken on three different ruminant species: goat, sheep and cow. The impact of the different steps of slide preparation was evaluated and we observed that the early steps, mainly sampling, freezing, cutting and staining of tissue, play a crucial role for a consistent success in capture of alveoli MEC from mammary sections.In this study, ® using two different frozen conditions, liquid nitrogen and cold isopentane, are shown in Figure ®/tissue/cryomold in liquid nitrogen results in loss of morphological details  obtained with or without OCTs Figure  and somes Figure . Rapid f® in liquid nitrogen  and RNA quantity. Usually, with goat and cow samples, we get 5 to 10 ng of RNA per cap . In other words, there are 3 picog RNA in 1/3 cell since we work on 8-μm tissue section thickness, and therefore one can estimate to ca. 10 picog the amount of RNA contained in one MEC. However with sheep, the amount of material we obtained was between 1.5 and 2 times higher.It is difficult to evaluate the exact number of MEC isolated after 40 to 60 min of LCM since this it depends on the number of acini present on the slide and on the MEC per acini (10 to >40). Given that the Veritas Arcturus system allows quantification of captured material via a tool estimating the total area selected before capture, we can establish a correlation between captured area  and different times of dehydration. HistoGene® stain is a special solution developed by Arcturus to stain tissues for LCM subsequently used as sources of RNA. It is a fast penetrating stain that provides good contrast by differential staining of nuclei (purple) and cytoplasm (light pink). Cresyl Violet® is a hydrophilic, basic stain that binds to negatively charged nucleic acids without water step during slide preparation to re-hydrate the tissue.The next step was to evaluate the impact of fixation, staining and dehydration on RNA integrity and yield as well as on tissue morphology. Previous studies ,38,44 ha® following the protocol recommended by Arcturus, (N°1) which easily distinguished the cytoplasm (stained in brown) and the nucleus , whereas neutral pH of Cresyl violet® solution (pH measured ~7) avoids degradation of RNA. After substitution of HistoGene® by RNase-free water (protocol N° 8), RNA degradation was reduced by less than one RIN unit. However, it was obviously not possible to recognize cells on unstained tissue sections. Given these results we decided to use the Cresyl violet® as stain for further experiments.Results are given in Table et al. [et al. have proposed to perform LCM under an argon atmosphere, thus preventing tissue rehydration to finally stabilize RNA [Dehydration is crucial to stabilize the tissue and to allow capture. All the steps following dehydration  are time consuming and it is necessary to keep tissues dehydrated to avoid degradation of RNA. A high ambient humidity could rehydrate the tissue and reactivate endogenous RNases. In addition, moisture impedes film adhesion and cell capture. For these reasons, we limit LCM to 45-60 minutes which proved to be a good compromise to overcome the variations in relative humidity. Ordway lize RNA . These a® (protocol N° 3) or RCL2®, are promising new noncrosslinking fixatives [® staining and could improve RNA quality. Actually, RNA degradation was especially reduced with RNA later® (loss of one RIN unit) whereas with RCL2® we observed a loss of 1.5 to 2.5 RIN units. However, RNA later® provokes a loss in morphology  such as RNA laterixatives , preservRNasin , a potent inhibitor of ribonucleases, was also tested prior to staining since such inhibitory activity was reported to protect RNA (included in staining solution) from degradation in LCM experiments for gene expression profiling of basal cell cancer tissues ,48. We dNevertheless, there was no considerable improvement in either quality or quantity of RNA recovered from the tissue sections after an inhibitor treatment. In conclusion, we finally decided to opt for protocol N° 7 (without any RNA protector) which is easier to handle and quicker to perform.qPCR experiments were performed on reverse transcribed RNA extracted from microdissected cells targeting specific gene transcripts to evaluate enrichment in MEC.Krt14) and MEC (LALBA and CSN1S2) was assessed after normalization, using PPAI and/or RPS24 as reference genes. FASN, a gene expressed in a large panel of tissues [LALBA (RQ mean = 1.47), CSN1S2 (RQ mean = 1.33) were significantly increased. FASN was relatively unchanged (RQ mean = 0.85), suggesting that active fatty acid synthesis which is required for energy utilization and membrane synthesis is equally expressed in MEC and in the surrounding tissue. These results attest to the enrichment in MEC after LCM even though increasing in LALBA and CSN1S2 transcripts are less striking, given the high percentage of MEC (around 80-90%) and the low number of other cell types in lactating mammary parenchyma sections.To determine potential cell contamination of the laser-captured cells by adjacent MMC or to estimate the selective capture of MEC, mRNA transcript levels of cell-specific markers were assessed by evaluating the relative expression between captured cells and their corresponding mammary tissue scrapes, after LCM. Relative quantity with specific markers for MMC  in the captured cells compared with the whole mammary tissue. A weak expression of Krt-14 was systematically observed in microdissected MEC, reflecting a slight contamination by MMC during capture. This is due to a very close proximity between MMC and MEC [CD3e (RQ mean = 0.14), a marker of lymphocytes and CD68 (RQ mean = 0.18) which suggests the putative presence of macrophages  to use to perform relative gene expression measurements made by qPCR? We chose to use isolated cells (each cap) against all scrape sections since it can be considered as a mean value of serial tissue sections.Typically, all these parameters have to be considered and the first one is usually accomplished through the use of endogenous housekeeping genes that are presumed to show stable expression levels in the samples under study. Which specific genes and how they can be measured in limited amounts of mRNA such as those extracted from microdissected cells still remains a concern. GeNorm software confirmed that LCM makes it possible to obtain highly MEC enriched material from lactating mammary tissue sections preserving RNA integrity. In addition, we provide molecular evidence for successful selectivity of the capture method despite the difficulty of disassociating luminal secretory cells (MEC) from MMC bordering the basal lamina which separates the epithelial layer from the extracellular matrix.FASN, a gene encoding the fatty acid synthase which is widely expressed in many tissues and cell types, including the alveolar secretory epithelium and adipose tissue. Relative proportions of these tissues, both involved in lipid metabolism, dramatically change during pregnancy.To accurately evaluate the expression of genes specifically expressed in MEC, such as those encoding LALBA and CSN1S2 represents a step forward in determining the transcriptional profile of a cell type and how it can be modulated by environmental factors such as feeding, stress, milking frequency, the health status or gene polymorphisms. In addition, to understand how genes expressed in several cell types are regulated, it is crucial to work on pure or at least enriched cell populations. Otherwise, expression analyses could potentially lead to artefactual results. This is well-exemplified by Capturing other cell types or stroma provides the opportunity to examine further to understand the mechanisms involved in growth regulation and morphogenesis of the mammary gland. Until now, most attention has been paid to the luminal epithelial cell which is the functionally active milk-producing cell and the most likely target cell for carcinogenesis. However attention on myoepithelial cells has begun to evolve with the recognition that these cells play an active part in branching morphogenesis and tumor suppression . HoweverqPCR: real time quantitative Polymerase Chain Reaction; MEC: Mammary Epithelials Cell; MMC: Mammary Myoepithelial Cell; RIN: RNA Integrity Number; RQ: Relative Quantification; RPS24: Ribosomal Protein S24; PPIA: cyclophylin A; Krt14: Cytokeratin 14; FASN: Fatty Acid Synthase; CSN1S2: αs2-casein; LALBA: α-lactalbumin;CB participated in study design, performed the LCM, RNA extraction and qPCR experiments, including statistical analyses, and drafted the manuscript. SM helped to perform the LCM and RNA extraction. JCH helped to perform qPCR and contributed to design qPCR systems. PD contributed to LCM protocol optimization. PM conceived the study and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.