Therefore, in addition to genetic alterations, changes in epigene

Therefore, in addition to genetic alterations, changes in epigenetic features such as CpG DNA methylation status of specific gene loci also mark the progress of cancers. Our current study showed that methylation of Wnt antagonist SFRP5 gene before treatment, independent of the genotype of EGFR gene, correlated with decreased progression free survival rate in NSCLC patients in response to the EGFR-TKI therapy. To our knowledge, this is the first report indicating that DNA methylation

Sotrastaurin chemical structure at specific gene loci in patient may predict drug response to the EGFT-TKI therapy. Both genetic and epigenetic risk factors for NSCLC have been studied extensively. Suzuki et al [23] has reported that methylation of the Wnt antagonist DKK3 correlated with low survival rate in NSCLC patients, despite of Selleck Poziotinib the different therapies patients received. However, in our study, we did not find significant difference in the EGFR-TKI responses between patient groups with or without methylated DKK3 (Additional file 1: Figure S2 and S3). In contrast, our results

suggested epigenotype of SFRP5 provide better prognostic estimation for the EGFR-TKI response, comparing to other Wnt antagonists. SFRP5 is a member of the SFRP protein family containing a cysteine-rich domain homologous to the putative Wnt-binding site of Frizzled proteins. It acts as soluble antagonist of Wnt signaling and is highly expressed in the retinal pigment epithelium, and moderately expressed in the pancreas (“”Entrez Gene: SFRP5 secreted frizzled-related protein 5″”). Previous studies has identified

association of SFRP5 promoter hypermethylation with Acute myeloid leukemia [29], ovarian cancer [30], gastric cancer [31], oral squamous cell carcinoma [32], pancreatic cancer [33] and breast cancer [34]. We found that hypermethylation of SFRP5 predicted worse outcomes of the EGFR-TKI therapy. Therefore, SFRP5 DNA methylation status may serve as Bortezomib molecular weight a prognostic molecular marker for appropriately predicting whether NSCLC patients would benefit from the EGFR-TKI therapy. Especially, it is interesting that in the subgroup with adenocarcinoma and EGFR mutation, patients with sFRP5 methylation have a significantly shorter PFS than those without sFRP5 methylation, While in nonsmokers without EGFR mutation, patients without sFRP1 methylation have a longer PFS compared with patients with its methylation(9.7 ms vs 2.0 ms, p = 0.05). Based on these results, we can make a hypothesis that activation of Wnt signaling by antagonist methylation could confer tumors the characters of stem cell, which consequently causes tumors resistant to EGFR TKIs therapy by generating acquired resistance, such as MET amplification or changes of PTEN tumor suppressor activity and so on. Further study is needed to validate this hypothesis. Conclusions In conclusion, our study revealed that sFRP5 may be an independent factor affecting PFS during long time maintenance of TKIs therapy.

The questions assessed the frequency and type of alcoholic bevera

The questions assessed the frequency and type of alcoholic beverage during the last year. Physical activity was assessed in minutes per day in accordance to time spent in various activities, including walking, dancing, and cycling among others, and computed for 1 week in the previous year during these activities. Height (cm) was determined by a stadiometer to the nearest 0.1 cm; weight (kg) was

assessed CX-5461 ic50 using a regularly calibrated scale to the nearest 0.1 kg; and the body mass index (BMI) was computed as weight (kg) divided by the square of the height (m2), usually defined as a BMI of 19–24.9, overweight 25–29.9, and obese >30. All other risk factors were self-reported. The questionnaire was originally used for the LAVOS study, terms were for clarification, and the instrument was standardized. We found a 16.5% nonrespondent rate during the survey. Radiology Lateral thoracic and lumbar spine radiographs were taken with a 40″” tube-to-film distance according to a standard protocol that included details concerning positioning of subjects and radiographic technique. Radiographs were taken with the subject in the left lateral position. The breathing technique was used for the thoracic films. The thoracic film was centered at T7 and the lumbar film at L2. All radiographic studies

were done in the same department and collected in our morphometry center in Mexicali. A sample of radiographs was sent to the same center early AZ 628 in the study to verify quality assessment and compliance with the protocol. All study radiographs were digitized using an AccuTab® table, and vertebral dimensions were measured

by placement of six points defining the margins of each vertebral body using a cursor with a peripheral device that enters the value of vertebral height in software specially designed to create a database. Six points were marked on each vertebral body from T4 to L4 to define vertebral shape and to describe three vertebral heights—Ha (anterior), Hm (medial), and Hp (posterior)—using the same criteria as SOF [12, 13]. The central reader was trained at the San Francisco Coordinating Center to ensure that the positioning Carnitine palmitoyltransferase II of points was similar to that used in the Study of Osteoporotic Fractures and the Beijing Osteoporosis Project [14]. To test the comparability of the method, a random sample of 10% of Mexican radiographies were sent to San Francisco for morphometric measurements. A good degree of agreement (kappa = 0.77, 95%CI 0.64–0.90) was found between readers at the San Francisco Coordinating Center at San Francisco and the Mexican Morphometry Center regarding the identification of normal and abnormal vertebras. Definition of vertebral deformity We used the modified Eastell criteria to define vertebral fracture, and we used the same criteria used in SOF to place the six points in each vertebra [15, 16].

PubMedCentralPubMed 5 Kaiser D, Robinson M, Kroos L: Myxobacteri

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formation by Streptomyces coelicolor. Microb Biotechnol 2011,4(2):175–183.PubMed 9. Diez J, Martinez JP, Mestres J, Sasse F, Frank R, Meyerhans A: Myxobacteria: natural pharmaceutical factories. Microb Cell Fact 2012, 11:52.PubMedCentralPubMed 10. de Lima Procopio RE, da Silva IR, Martins MK, de Azevedo JL, de Araujo JM: Antibiotics produced by Streptomyces. Braz J Infect Dis 2012,16(5):466–71. 11. Bentley SD, Chater KF, Cerdeno-Tarraga

AM, Challis GL, Thomson NR, James KD, Harris DE, Quail MA, Kieser H, Harper D, et al.: Complete genome sequence of the model actinomycete Streptomyces coelicolor A3(2). Nature 2002,417(6885):141–147.PubMed 12. Goldman BS, Nierman WC, Kaiser D, Slater SC, Durkin AS, Eisen JA, Ronning CM, Barbazuk WB, Blanchard M, Field C, et al.: Evolution of sensory complexity recorded in a myxobacterial genome. Proc Natl Acad Sci USA 2006,103(41):15200–15205.PubMedCentralPubMed VS-4718 purchase 13. Saier MH Jr: A functional-phylogenetic classification system for transmembrane solute transporters. Microbiol Mol Biol Rev 2000,64(2):354–411.PubMedCentralPubMed 14. Martin JF, Sola-Landa A, Santos-Beneit F, Fernandez-Martinez LT, Prieto C, Rodriguez-Garcia A: Cross-talk of global nutritional regulators in the control of primary and secondary metabolism in Streptomyces. Microb Biotechnol 2011,4(2):165–174.PubMed ID-8 15. Chater KF, Biro

S, Lee KJ, Palmer T, Schrempf H: The complex extracellular biology of Streptomyces. FEMS Microbiol Rev 2010,34(2):171–198.PubMed 16. Youm J, Saier MH Jr: Comparative analyses of transport proteins encoded within the genomes of mycobacterium tuberculosis and mycobacterium leprae. Biochim Biophys Acta 2012,1818(3):776–797.PubMedCentralPubMed 17. Saier MH Jr, Tran CV, Barabote RD: TCDB: the transporter classification database for membrane transport protein analyses and information. Nucleic Acids Res 2006,34(Database issue):D181–186.PubMedCentralPubMed 18. Saier MH Jr, Yen MR, Noto K, Tamang DG, Elkan C: The transporter classification database: recent advances. Nucleic Acids Res 2009,37(Database issue):D274–278.PubMedCentralPubMed 19. Saier MH Jr: Protein secretion and membrane insertion systems in gram-negative bacteria. J Membr Biol 2006,214(2):75–90.PubMed 20.

References 1 Cornelis GR: The type III secretion injectisome Na

References 1. Cornelis GR: The type III secretion injectisome. Nat Rev Microbiol 2006,4(11):811–825.CrossRefPubMed 2. Subtil A, Parsot C, Dautry-Varsat A: Secretion of predicted Inc proteins

of Chlamydia pneumoniae by a heterologous type Selleck H 89 III machinery. Mol Microbiol 2001,39(3):792–800.CrossRefPubMed 3. Valdivia RH: Chlamydia effector proteins and new insights into chlamydial cellular microbiology. Curr Opin Microbiol 2008,11(1):53–59.CrossRefPubMed 4. Bavoil P, Hsia R-C: Type III secretion in Chlamydia : a case of déjà vu? Mol Microbiol 1998, 28:860–862.CrossRefPubMed 5. Fields KA, Hackstadt T: Evidence for the secretion of Chlamydia trachomatis CopN by a type III secretion mechanism. Mol Microbiol 2000,38(5):1048–1060.CrossRefPubMed 6. Betts HJ, Twiggs LE, Sal MS, Wyrick PB, Fields KA: Bioinformatic and biochemical evidence for the identification of the type III secretion system needle protein of Chlamydia trachomatis. J Bacteriol 2008,190(5):1680–1690.CrossRefPubMed 7. Fields KA, Mead DJ, Dooley CA, Hackstadt T:Chlamydia trachomatis type III secretion: evidence for a functional apparatus during early-cycle development. Mol Microbiol 2003,48(3):671–683.CrossRefPubMed

8. Dautry-Varsat A, Subtil A, Hackstadt T: Recent insights into the mechanisms of Chlamydia entry. Cellular Microbiology 2005,7(12):1714–1722.PubMed Doramapimod 9. Carabeo RA, Grieshaber SS, Fischer E, Hackstadt T:Chlamydia trachomatis induces remodeling of the actin cytoskeleton during attachment and entry into HeLa cells. Infect Immun 2002,70(7):3793–3803.CrossRefPubMed 10. Carabeo

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Moreover, since brain endothelia associate principally with lamin

Moreover, since brain endothelia associate principally with laminin 1 and 2, not present in epithelia and endothelia elsewhere [13, 34, 35], we postulate that the observed CNS tropism of pknD may be due to its interaction with CNS-associated laminin isoforms. Bacterial STPKs are candidates for sensing the environment and regulation of microbial metabolic states [36, 37]. The M. tuberculosis

PknD intracellular kinase has been previously demonstrated to associate with and phosphorylate intracellular targets including MmpL7 [38] and the putative anti-anti-sigma factor Rv0516c, regulating sigF-associated genes [39]. M. tuberculosis sigF is an alternative sigma factor implicated in stress response, stationary phase, dormancy, and late-stage disease in vivo [40, 41]. Our previously published data demonstrate Selleck ALK inhibitor that M. tuberculosis significantly down-regulate transcription, protein synthesis, and energy metabolism see more very early after invasion by brain endothelia [42]. These data raise the possibility that interaction with the host CNS may mediate bacterial signaling. The two domain structure of PknD invites the hypothesis that an extracellular signal, possibly a host factor,

may induce an intracellular cascade via activity of the kinase and regulation of sigF. An ortholog of M. tuberculosis pknB in Bacillus subtilis has been demonstrated to regulate bacterial dormancy by a similar mechanism [43, 44]. The potential induction of sigF-mediated cellular activity via pknD could confer upon M. tuberculosis a survival advantage in unique conditions such as the brain endothelium. M. tuberculosis are well known to adapt to a quiescent dormant state. However, the precise location of dormant bacilli during human latent

TB Clomifene infection remains elusive. Immune surveillance of foreign antigens is relatively limited in the CNS [20, 45], and mycobacteria escape immune recognition following direct inoculation into the brain parenchyma [46]. We therefore postulate that the unique microenvironment in the CNS is advantageous for bacterial survival, and may provide a sanctuary to dormant M. tuberculosis. While this study examines and indicates a role for M. tuberculosis pknD in the initial stages of invasion and infection, the role of dormancy in CNS disease will be an active area of research for our future studies. Given the above data, we hypothesize that interaction of PknD protein with a host extracellular factor, possibly laminin, facilitates adhesion of M. tuberculosis to the microvascular endothelium of the CNS. Other neurotropic pathogens have been shown to trigger host-mediated uptake and internalization of bacteria through cytoskeletal rearrangement, thus this represents a possible mechanism for future study [47, 48].

05) However, as TIMP3 mRNA expression was very low in each of th

05). However, as TIMP3 mRNA expression was very low in each of the four cell lines, a significant correlation between miR-21 and TIMP3 mRNA was not detected (data not shown). Figure 3 TIMP3 protein expression correlates with microRNA-21 content in breast cancer cell lines in vitro. A, Western blot analyses of TIMP3 protein, performed

as described in Methods. B, Correlation between miR-21expression and TIMP3 protein levels (Pearson correlation = -0.905; P < 0.05). The TIMP3 3'-UTR is a target for miR-21 To determine whether suppression of miR-21 impacts TIMP3 transcription, we quantified TIMP3 mRNA in MDA-MB-231 and MDA-MB-435 cells (each expressing high levels of endogenous miR-21) following knockdown of miR-21 expression. Down-regulation of endogenous miR-21 (Fig. 4A) led to a 1.3 and 1.4 fold increase in TIMP3 mRNA in MDA-MB-231 and MDA-MB-435 cells, respectively (Fig. 4B). Similar increases in TIMP3 protein expression following miR-21 knockdown were observed (Fig. 4C, 4D). These data suggest that TIMP3 is regulated

by miR-21 in breast cancer cells. In order to determine whether the 3′untranslated region of TIMP3 selleck products mRNA is a direct functional target of miR-21, we cloned a 250 bp TIMP3 3′-UTR segment, which includes a potential target site for miR-21 (Fig. 4E), downstream of the pGL3 luciferase reporter gene to generate the pGL3-timp3 vector. This vector was co-transfected into MDA-MB-435 or MDA-MB-231 cell lines together with anti-miR-21 oligonucleotides or miRNA negative control. A renilla luciferase vector (pRL-TK) was used to normalize differences in transfection efficiency. Luciferase activity in MDA-MB-435 cells co-transfected with pGL3-timp3 vector and anti-miR-21 oligonucleotides significantly increased by 38% when compared with negative control (P < 0.05), whereas luciferase activity in MDA-MB-231 cells increased by only 20% (Fig. 4F). These data demonstrate Aspartate that miR-21 regulates TIMP3 expression at the transcriptional level. Figure 4 miR-21 regulates TIMP3 expression at the mRNA and protein level by targeting the 3′untranslated region of TIMP3 mRNA. A, miR-21 expression was analyzed by TaqMan

PCR in MDA-231 and MDA-435 cells following transfection with anti-miR-21 or control oligonucleotides, as in Fig. 2B. B, Relative TIMP3 mRNA expression was analyzed in MDA-231 and MDA-435 cells as described in Methods, following miR-21 silencing as performed in A. C, Western blot analysis of TIMP3 protein expression in MDA-231 and MDA-435 cells following miR-21 silencing as performed in A. D, Quantification of relative TIMP3 protein expression in MDA-231 and MDA-435 cells following miR-21 silencing, as performed in A. E, Generation of cDNA encoding the 3′UTR region of TIMP3 containing a miR-21 binding site. cDNA was subsequently cloned into a Luciferase reporter plasmid. F, Determination of the impact of miR-21 silencing on pGL3-TIMP3 luciferase expression in MDA-231 and MDA-435 cells.

Closed circles: M tuberculosis carrying the plasmid pMV261 (empt

Closed circles: M. tuberculosis carrying the plasmid pMV261 (empty vector control); squares: M. tuberculosis carrying the plasmid pMVOBG (plasmid overexpressing Obg). The data shown are representative findings from three different. experiments. Conclusion Our data reveal that M. tuberculosis Obg has characteristics that are common this website to its homologues in other bacteria, in addition to properties that are unique. Generation and characterization of mutant alleles of M. tuberculosis Obg should provide additional insights to the

role of Obg in this important human pathogen, and toward identification of antimicrobials that reduce its ability to promote M. tuberculosis survival. Methods Bacteria and yeast strains and their growth conditions M. tuberculosis H37Rv was grown either MK-8776 nmr in Middlebrook 7H9 broth medium containing Tween (0.05%) and OADC (10%) (7H9-TW-OADC) broth, or in Middlebrook 7H10 agar medium containing Tween (0.05%) and OADC (10%) (7H10-TW-OADC). M.

tuberculosis strains harboring plasmids were grown in the above media containing the antibiotic kanamycin (25 μg/ml) or hygromycin (50 μg/ml). E. coli strains containing plasmids were grown in LB broth or LB agar plates with the antibiotic(s) ampicillin (100 μg/ml), kanamycin (25 μg/ml) or both. Unless specified, all bacteria were grown at 37°C. The yeast strain AH109 was grown at 30°C in YPD broth or in agar supplemented with adenine hemisulphate (0.003%). DNA manipulation Chromosomal DNA of M. tuberculosis H37Rv was isolated using cetyl trimethyl ammonium bromide (CTAB). Plasmid DNA from E. coli was isolated using Qiaprep kit (Qiagen Inc.). PCR reactions were performed as described by Ausubel et al [45], with genomic DNA of M. tuberculosis H37Rv used as the template for amplifying coding regions of its genes. Oligonucleotide

primers (Table 2) were synthesized at the Center for DNA Technology at The University of Texas Health Science Center at San Antonio. Pyruvate dehydrogenase Table 2 List of primers used in this study. Primer name Primer sequence Gene TBOBG1 CCGCATATGAAGGGGAGCTCGGTGCCT CGG Obg TBOBG2 CGTCCGGATCCGGACTTCTCATCAGCCATCCCC Obg TBOBG5 CCGCAGGATCCGCACACTCCGCAGATGAAGGGGAGCTCGGTG Obg TBOBG6 ATGAAGGGATCCTCGGTGCCTCGGTTTGTCGATCGGGTC Obg TBRELAF ACGCATATGGCCGAGGACCAGCAGCTCACGGCGCAAGCG RelA TBRELAR ATGGGATCCTGCGTCTGCTCGGCGGAGAAAAGCGCG RelA Underlined nucleotides indicate the restriction sites created in the primers. CATATG, NdeI and GGATCC, BamHI. To generate an Obg overexpression construct, we amplified the whole gene coding for Obg of M. tuberculosis by PCR with primers TBOBG1 and TBOBG2. These primers were designed to have an NdeI site at the 5′nd (TBOBG1) and a BamHI site at the 3′nd (TBOBG2). The DNA fragment obtained was cut with NdeI and BamHI and ligated to a similarly cut pET16b vector to create the plasmid pTBOBGE. In addition, we created several other plasmids to express Obg or other proteins in mycobacteria or yeast.

LM, and KB, provided the clinical samples and collected clinical

LM, and KB, provided the clinical samples and collected clinical information and MR participated in the coordination of the study and helped to draft the manuscript. JV performed the statistical Luminespib mw analysis. All authors

read and approved the final manuscript.”
“Introduction Gastric cancer was one of the major causes of mortality in the world, especially in Asian countries. So far, the pathogenic mechanism underlying gastric carcinogenesis was not fully elucidated. MicroRNAs (miRNAs) were a class of 22-nucleotide noncoding RNAs, which might function as regulators of gene expression [1]. More and more evidences showed that miRNAs might play important roles in various biological processes, including cell proliferation, apoptosis, tumorigenesis and MDR of cancer [2]. So far, the functions of gastric cancer related miRNAs were not clear. MiR-27a might mediate drug resistance of esophageal cancer cells through regulation of MDR1 and apoptosis [3]. However, the role of miR-27a in gastric cancer was not reported yet. To our knowledge, here we have firstly investigated the role of miR-27a in proliferation and multidrug resistance of gastric cancer cells. see more Materials and methods Cell culture Human gastric cancer cell line, MKN45, was routinely maintained in DMEM medium (GIBCO, Carlsbad, CA,

USA) supplemented with 10% fetal bovine serum at 37°C in humidified air containing 5% carbon dioxide air atmosphere. MiRNA transfection Cells were plated in plates and cultured for 16 h, and then transfected with the antagomirs of miR-27a or control RNA (Lafayette, CO) as described previously [3]. Real-time

PCR Total RNAs from cells were extracted and cDNA synthesis and amplification were performed as described previously [4]. Primers were designed as: MDR1, forward: 5′-CCCATCATTGCAATAGCAGG-3′, reverse: 5′-TGTTCAAACTTCTGCTCCTGA-3′; cyclinD1, forward: 5′-GGAGCTGCTCCTGGTGAACA-3′, reverse: 5′-TGTTGGGGCTCCTCAG GTTCA-3′; P21, forward: 5′-CCCGTGAGCGATGGAACT-3′, reverse: 5′-CGAGGCACAAGGG TACAAGA-3′; P27, forward: 5′-CAAGTACGAGTGGCAAGAGG-3′, reverse: 5′-GTAGAA GAATCGTCGGTTGC-3′. Comparative real-time PCR Rucaparib cost was performed in triplicate, including no-template controls. Relative expression was calculated using the comparative Ct method. Cell growth assay Cells were seeded on a 96-well plate at 3 × 104 cells/well. Each sample has four replicates. Viable cells were counted by the MTT assay after 2, 4, 6, and 8 days. Soft agar assay Soft agar assay was performed as described previously [5]. Each assay was performed in triplicate. Tumor growth in nude mice Female athymic nu/nu mice, 5-6 weeks of age, were used in the experiment. The cells were resuspended in D’Hanks solution, and 5 × 106 cells in 0.2 ml were injected subcutaneously into the right flank of 4-week-age mice. Experimental and control groups had at least 6 mice each. Tumors were measured twice weekly, and the tumor volume was calculated.

The dose-corrected steady-state

The dose-corrected steady-state Selleckchem IWP-2 trough dabigatran concentration of the single

individual treated with phenytoin and phenobarbitone (0.04 µg/L per mg/day, in the individual with a trough concentration of 9 µg/L on dabigatran etexilate 110 mg twice daily) was notable as it was more than 3 SD below the mean dose-corrected trough concentration of our study population (0.32 µg/L per mg/day, which is equivalent to 70 µg/L on 110 mg twice daily). Further, it is well below target trough dabigatran concentrations that have been suggested in the literature; for example, Chin et al. [54] have proposed 30–130 µg/L. While phenytoin and phenobarbitone are known P-gp inducers, the impact of concomitant use on the pharmacokinetics of dabigatran has not previously been reported [55]. Rifampicin, another P-gp inducer, has been demonstrated to reduce dabigatran concentrations by around 67 % [10]. To our knowledge, these are the first data to support the notion that phenytoin and/or phenobarbitone have a significant effect on dabigatran concentrations. 4.1 Limitations Our study has several limitations. Firstly, the primary

aim, to assess and compare the correlations of the renal function equations with trough plasma dabigatran concentrations, may have been better addressed by gathering data from individuals given intravenous dabigatran. From such data, true dabigatran clearance could have been calculated, without the need to consider oral availability, which is affected by many covariates (see Table 1). The bias and imprecision of the renal function equations against dabigatran clearance Amino acid could then have been check details compared. However, this approach would also have been more challenging logistically. By comparison, trough concentrations are a convenient and useful representation of apparent oral clearance with which to compare the equations, as these have been correlated with the risk of thromboembolic and haemorrhagic outcomes in the setting of AF [4]. Secondly, there could be a statistical power problem since we had a dataset of only 52 individuals. By comparing

the equations with the lowest and highest R 2 for the multiple linear regression model for trough plasma dabigatran concentrations (CG and CKD-EPI_CrCys, respectively), we calculate that, for future studies, around 680 subjects are needed to have 80 % power (α = 0.05) to detect a difference between these two equations. This is valuable data to inform the conduct of future studies. Thirdly, we did not measure the active precursor of dabigatran, BIBR 951, or the active metabolites of dabigatran, its glucuronides [15]. While BIBR 951 is thought to have concentrations <0.4 % of those of dabigatran [15], the dabigatran glucuronides have been reported to make up 10–35 % of the total active drug concentrations following ingestion of dabigatran etexilate [7, 12, 15, 16, 56, 57].


99% of bacterial cells in the biofilm matrix were di


99% of bacterial cells in the biofilm matrix were dispersed into single cells. The dispersed biofilm cells were then diluted in 1× PBS (with 0.5% BSA) for IMS. Immuno-magnetic separation AZD8186 nmr One milliliter of samples was incubated with 10 μl anti-E. coli antibody (ViroStat, Portland, ME) for 10 min with gentle shaking. Bacterial cells were pelleted by centrifugation (3,300 × g, 4°C, 3 min) and re-suspended in 100 μl separating buffer (1× PBS, 0.5% BSA, 2 mM EDTA, pH 7.4) (EDTA: ethylenediaminetetraacetic acid). 10 μl streptavidin microbeads (Miltenyi Biotec, Auburn, CA) were added and incubated at 4°C in the dark for 10 min. Separation of E. coli cells was performed in LS columns and a midi MACS® separator (Miltenyi Biotech, Auburn, CA) following the protocol provided by the manufacturer, except that one more washing step was added to remove more S. maltophilia cells. In a two-step IMS, enriched cells from the first step IMS were directly transferred into a new LS column for the second separation. Densities of E. coli and S. maltophilia cells in samples and IMS enriched collections were measured using a plate-counting method with selective agar. Cell densities were used to calculate recovery and purity of E. coli after IMS. The protocol was

amended with the use of RNAlater when enriched cells were used for microarray study. Bacterial cells were re-suspended in RNAlater rather than PBS after sample collection and kept at 4°C overnight, GANT61 supplier followed by homogenization. RNAlater was removed

and cells were re-suspended in separating buffer just before IMS. During column separation, the buffer was additionally supplied with 10% (v/v) RNAlater. Enriched cells were immediately stored in RNAlater. The whole procedure was performed at 4°C. All buffers, reagents, and pipette tips were nuclease-free MycoClean Mycoplasma Removal Kit and pre-cooled. Microarray study Pure E. coli cultures were used to evaluate the effect of separation on the transcriptome by microarray analysis. Suspended E. coli cultures were harvested from an annular reactor (1320 LJ, BioSurface Technologies, Bozeman, MT), supplied with 0.1× LB broth (100 ml/h) for 7 days after inoculation. Aggregates were removed from broth cultures by filtration (5.0 μm Millipore, Billerica, MA). Suspended E. coli cells were immediately re-suspended in RNAlater and stored at 4°C overnight. One aliquot of RNAlater stored E. coli cells served as the control (“”unsorted”" cells) and was kept in RNAlater without further treatment. The other aliquot was treated to acquire “”sorted”" cells as described above using the amended protocol. Samples collected independently from a second annular reactor served as a biological replicate for the microarray study. RNAlater was removed by filtration with a membrane (0.22 μm, Millipore, Billerica, MA) from E. coli cells just before RNA extraction for both “”unsorted”" and “”sorted”" cell collections.