Drosophila melanogaster large conductance calcium-activated potassium channel SLOWPOKE (SLO) undergoes modulation via its binding partner SLO-binding protein (SLOB). Regulation of SLO by SLOB influences the voltage dependence of SLO activation and modulates synaptic transmission. SLO and SLOB are expressed especially prominently in median neurosecretory cells (mNSCs) in the pars intercerebralis (PI) region of the brain; these cells also express and secrete Drosophila insulin like peptides (dILPs). Previously, we found that flies lacking SLOB exhibit increased resistance to starvation, and we reasoned that SLOB may regulate aspects of insulin signaling and metabolism. Here we investigate the role of SLOB in metabolism and find that slob null flies exhibit changes in energy storage and insulin pathway signaling. In addition, slob null flies have decreased levels of dilp3 and increased levels of takeout, a gene known to be involved in feeding and metabolism. Targeted expression of SLOB to mNSCs rescues these alterations in gene expression, as well as the metabolic phenotypes. Analysis of fly lines mutant for both slob and slo indicate that the effect of SLOB on metabolism and gene expression is via SLO. We propose that modulation of SLO by SLOB regulates neurotransmission in mNSCs, influencing downstream insulin pathway signaling and metabolism.There is ample evidence that ion channel modulation by accessory proteins within a macromolecular complex can regulate channel activity and thereby impact neuronal excitability. However, the downstream consequences of ion channel modulation remain largely undetermined. The  Drosophila melanogaster BK channel is encoded by the slowpoke (slo) gene Slo-binding) that we isolated by a yeast two-hybrid screen using the extended carboxyl-terminal tail domain of SLO as bait pars intercerebralis (PI) region of the fly brain Drosophila insulin-like peptides (dILPs) slob mutant fly lines with dramatically decreased SLOB expression show prolonged survival under conditions of complete food-deprivation slob null flies exhibit altered locomotor activity during starvation . Wild-type flies typically exhibit an extended period of activity under starvation conditions; such hyperactivity is thought to reflect an adaptive foraging strategy in response to diminished food availability Slob null flies lack this hyperactive response, suggesting a role for the SLO/SLOB complex in mNSCs in integrating food stimuli and coordinating a response to nutrient conditions.Large conductance, calcium- and voltage-sensitive potassium channels (BK channels) play a critical role in the regulation of neuronal excitability and neurotransmitter release. The Drosophila melanogaster: dILP 1–7 dilp2, dilp3, and dilp5 are expressed in mNSCs of adult flies Altered insulin/insulin-like growth factor signaling (IIS) has also been implicated in increased resistance to starvation slob and slo are both regulated in a circadian manner takeout (to) encodes a protein similar to juvenile hormone binding protein and also cycles with a daily rhythm To is expressed in structures related to feeding, such as the cardia, crop, antennae, and head fat body To mutant flies are hyperphagic and exhibit alterations in energy storage Interestingly, slob mutant flies exhibit alterations in downstream measures of insulin signaling, as well as differences in energy storage. In addition, we present evidence that lack of SLOB in mNSCs results in dramatic changes in gene expression of to and dilp3. Interestingly, the effect of SLOB on metabolism appears to depend on SLOB's effect on to expression level. Importantly, intact SLO function is necessary for changes manifested in the slob null phenotype, implying that the modulation of SLO by SLOB mediates the alterations in gene expression and metabolism.Here we sought to determine how SLOB expression in mNSCs influences insulin pathway signaling and metabolism. We find that 1to mutant flies exhibit decreased resistance to starvation slob null flies also exhibit a starvation phenotype, surviving significantly longer than wild-type control flies during starvation stress to expression is altered in slob null flies. To this end, to transcript levels were measured in control (P41WT) and slob null (IP1slob) fly heads, as well as in rescue lines expressing SLOB specifically in mNSCs. Two rescue lines in the IP1slob background were examined. The mai301-GAL4 driver targets expression to mNSCs, as well as some additional neurons dilp2-GAL4 driver line is specific for the dilp-expressing mNSCs to transcript levels are significantly upregulated in IP1slob fly heads, and this effect is rescued by expression of SLOB in mNSCs, regardless of the driver  was measured in P41WT and IP1slob fly heads. InR activation results in downstream phosphorylation of AKT at Ser 505 in Drosophila, which is homologous to phosphorylation of AKT at Ser 473 in mammals IP1slob flies   . Therefo41 flies , 6D. Who1to flies, as well as in IIS pathway mutant flies IP1slob flies exhibit increased storage of triglycerides compared to P41WT flies, and this effect is rescued by expression of SLOB in mNSCs , the effect is significantly attenuated compared to dilp3 downregulation in IP1slob heads. Therefore, the effect of SLOB on dilp3 expression functions at least in part through modulation of SLO.We also measured  reduced . Althougslob null flies live significantly longer than control flies under conditions of complete food deprivation to are upregulated almost five-fold in slob null flies, and this effect is rescued by expression of SLOB targeted specifically to mNSCs. Using RNAi to decrease SLOB levels results in a similar increase, even when SLOB knockdown is targeted to mNSCs. Furthermore, overexpression of SLOB either ubiquitously or specifically in mNSCs downregulates to levels. We confirmed that TO protein levels are similarly upregulated in slob null flies. The mechanism underlying regulation of to in response to SLOB levels in mNSCs is unclear. Since mNSCs project to the CC and the dorsal blood vessel, it is likely that there are several steps between SLOB regulation of mNSCs and its downstream effects on to expression in areas of the head such as the fat body. Like slob, levels of to are regulated by the circadian clock to levels are elevated at all time points in slob null flies, to still cycles in the absence of SLOB, suggesting that factors other than SLOB influence circadian regulation of to. PAR domain protein 1 (PDP1ε) is a circadian transcription factor reported to indirectly regulate to expression pdp1ε transcript levels are not significantly different between control and slob null flies (data not shown). TO protein levels also cycle in slob null flies. Expression levels were measured under LD conditions however, and TO protein expression is directly regulated by light slob null flies.Previously, we found that to mutant flies die faster during starvation to expression, we conclude that upregulation of TO in slob null flies mediates starvation resistance. In addition, slob null flies exhibit increased storage of triglycerides, which may enable them to withstand longer durations of starvation. To mutant flies are hyperphagic and also exhibit increased energy storage; however they cannot harness this energy during periods of starvation, resulting in early death slob null background, either through SLOB rescue in mNSCs or through mutation of to, restores triglyceride levels to those of control flies, suggesting that metabolic changes due to the lack of SLOB are mediated by TO. Likewise, fly lines which exhibit low levels of to relative to slob null flies also exhibit increased levels of trehalose compared to slob null flies, suggesting that TO regulates sugar levels as well. The mechanism underlying TO-mediated changes in metabolism is still not entirely clear; TO is secreted into the hemolymph and shares sequence similarity with juvenile hormone binding protein (JHBP) It has been proposed that TO may link circadian and feeding behaviors. Of note, dilp2 expression in slob null flies. Surprisingly, we discovered a striking decrease in dilp3 levels in slob null flies. This effect is due to SLOB in mNSCs, since it is rescued by specific expression of SLOB in mNSCs. Conversely, overexpression of SLOB in mNSCs results in dramatically upregulated levels of dilp3, suggesting that SLOB in mNSCs positively regulates dilp3 expression. How might changes in SLOB expression regulate dilp3 transcript levels? Dilp3 transcription undergoes autocrine regulation, whereby dILP signaling through InRs expressed by mNSCs results in downstream sequestration of the transcription factor dFOXO to negatively regulate transcription of dilp3, but not dilp2 or dilp5dilp3 expression will be downregulated by elevated IIS resulting from increased release of dILPs from mNSCs  in pancreatic islet beta cells  subunit of the KATP channel in mNSCs ATP blocker, demonstrating that adult mNSCs display electrophysiological properties similar to beta cells. Interestingly, a role for BK channels in mammalian insulin secretion has recently come back into favor. BK channel knock-out mice exhibit broadened single action potentials in beta cells and reduced glucose-stimulated insulin release slob null flies, wherein SLO activity is elevated slob null flies are consistent with enhanced release of dILPs from mNSCs . Generation of wild-type control (P41WT), slob null (IP1slob), slob rescue flies expressing slob in mNSCs , UAS-slob, and UAS-slob-RNAi flies in the yw background was described in detail previously IP1slob flies were obtained from the imprecise excision of a P-element insertion in the slob gene; they express no SLOB. The P41WT fly line was obtained from precise excision of the P-element and serves as a control for the IP1slob line. IP1Slob flies do not exhibit any gross growth or developmental defects. Multiple isoforms of slob exist slob57 is the most prominent isoform. In these studies slob57 was used for expression or RNAi knockdown and is referred to simply as slob in these lines. Actin-GAL4, mai301-GAL4, and 1ry506,to (1to) lines were provided by Dr. Amita Sehgal (University of Pennsylvania), and dilp2-GAL4 by Dr. Eric Rulifson . 1To flies have a deletion in the 3′ region of to genomic DNA, resulting in very low levels of basal expression and rendering mutants incapable of regulating to expression in response to starvation 1slo1St (1slo) and dilp31slo is available, but it has been used extensively as a slo mutant line and exhibits electrophysiological and circadian phenotypes Dilp3 is undetectable by qPCR in dilp3 mutant flies (data not shown). Dilp2-GAL4 and dilp3 lines were outcrossed into the yw background seven times and a series of crosses were then conducted to generate the following lines: P41,dilp3WT; IP1, dilp3slob; and IP1,dilp2>slobslob, a second rescue line expressing slob specifically in insulin producing neurons in the PI region (mNSCs). Additional crosses were conducted to create the following lines: P41,slo1WT; IP1,slo1slob; and IP1,to1slob lines. UAS-slob and UAS-slob-RNAi lines were maintained as homozygous lines and crossed to GAL4 driver lines prior to experimentation.Fruit flies were cultured at 25°C on standard RL32.Total RNA was extracted from a minimum of 30 fly heads using the UltraSpec RNA isolation system following the manufacturer's recommendations (Biotecx Laboratories). 2 µg of RNA was reverse transcribed using the High Capacity RNA-cDNA kit (Applied Biosystems). QPCR was performed on an Applied Biosystems 7000 detection system using Power SYBR green master mix and 1 ng template cDNA. Primers were designed using the Primer Express software (Applied Biosystems). Primer sequences are available upon request. Results were calculated for a minimum of three independent RNA extractions using the standard curve method and normalized to the ribosomal gene, Drosophila P-AKT , rabbit polyclonal anti-pan AKT , rabbit polyclonal anti-MAPK (Sigma-Aldrich), and rabbit polyclonal anti-β-actin . Following washes with TBST, blots were incubated with horseradish peroxidase-conjugated donkey anti-rabbit or anti-rat secondary antibody, washed again with TBST, and visualized using the Enhanced Chemiluminescence Detection System . The optical densities for proteins of interest were quantitated using NIH Image and normalized to the loading control MAPK. Furthermore, in 6 of 8 experiments in the PAKT data set, proteins were also normalized to β-actin.At least 30 fly heads were homogenized in lysis buffer containing 1% CHAPS, 20 mM Tris-HCl pH 7.5, 10 mM EDTA, 12 mM NaCl, 50 mM KCl, protease inhibitor cocktail (Sigma-Aldrich) and phosphatase inhibitor cocktail (Sigma-Aldrich) at 4°C. Flies were starved with 1% agar for 30 min prior to protein extraction for analysis of phosphorylated AKT (P-AKT), in order to establish a baseline regardless of food ingested immediately before protein extraction. Equivalent amounts of protein were separated on 4–12% Tris-Bis gradient gels and transferred to nitrocellulose blots. Blots were blocked with 5% nonfat milk in TBST  and probed with primary antibodies overnight. The following primary antibodies were used: rabbit polyclonal anti-SLOB To measure circulating trehalose and glucose, hemolymph was extracted by decapitation and centrifugation from adult female flies after a 5 hr starvation with 1% agar as previously described Triacylglycerides (TAG) were measured in adult female flies as described previously with slight modifications


Reliable and long-term expression of transgenes remain significant challenges for gene therapy and biotechnology applications, especially when antibiotic selection procedures are not applicable. In this context, transposons represent attractive gene transfer vectors because of their ability to promote efficient genomic integration in a variety of mammalian cell types. However, expression from genome-integrating vectors may be inhibited by variable gene transcription and/or silencing events. In this study, we assessed whether inclusion of two epigenetic control elements, the human Matrix Attachment Region (MAR) 1–68 and X-29, in a piggyBac transposon vector, may lead to more reliable and efficient expression in CHO cells. We found that addition of the MAR 1–68 at the center of the transposon did not interfere with transposition frequency, and transgene expressing cells could be readily detected from the total cell population without antibiotic selection. Inclusion of the MAR led to higher transgene expression per integrated copy, and reliable expression could be obtained from as few as 2–4 genomic copies of the MAR-containing transposon vector. The MAR X-29-containing transposons was found to mediate elevated expression of therapeutic proteins in polyclonal or monoclonal CHO cell populations using a transposable vector devoid of selection gene. Overall, we conclude that MAR and transposable vectors can be used to improve transgene expression from few genomic transposition events, which may be useful when expression from a low number of integrated transgene copies must be obtained and/or when antibiotic selection cannot be applied. Efficient gene transfer and expression for functional studies, protein production or gene and cell therapies usually requires reliable DNA delivery and transcription into target cells. Gene transfer methods based on viral and non-viral vectors have been developed to maximize gene delivery and expression, but an expression system combining high levels of reliability, efficacy and safety is currently lacking. For instance, non-viral vectors are associated with a reduced risk of insertional mutagenesis when compared to e.g. retroviral vectors for gene or cell therapies, and they are easier to produce in vitroGenome integration is usually a requisite for persistent transgene expression in dividing cells. Integration can be mediated by cellular activities when plasmid vectors are used. For instance, stable transfection relies on the selection of rare cells having integrated plasmid DNA into one or few genomic loci, as a result of the action of cellular DNA repair and recombination enzymes Alternatively, DNA recombination enzymes such as transposases, viral integrases, or synthetic integrases may be expressed transiently in target cells or introduced together with the transgene-bearing DNA to assist transgene integration. This usually yields increased frequencies of transgene integrations when compared to plasmid vectors. Among these are the proteins mediating targeted genomic DNA cleavage, such as the meganucleases and zinc finger nucleases that allow DNA integration in particular genomic loci, in contrast to the more random integration events mediated by viral integrases and transposases Among non-viral vectors, transposons are particularly attractive because of their ability to integrate single copies of DNA sequences with high frequency at multiple loci within the host genome Epigenetic regulatory elements can be used to protect the transgene from unwanted epigenetic effects when placed near the transgene on plasmid vectors. For example, elements called matrix attachment region (MARs) were proposed to increase transgene genomic integration and transcription while preventing heterochromatin silencing, as exemplified by the potent human MAR 1–68 Transposition efficiency varies significantly depending on the transposon system and cell type. Therefore, we first determined optimal transfection conditions for our model CHO cells. Different quantities and ratios of plasmid bearing the puromycin resistance-carrying transposon and of the PB transposase expression vector were co-transfected into cultured cells, and the occurrence of antibiotic-resistant colonies were scored , as perfAs antibiotic resistance does not necessarily reflect efficient transgene expression, we next used the green fluorescent protein (GFP) expressed from a strong GAPDH cellular promoter derivative as an indicator. To test whether adding a MAR element to the PB transposon may affect transposition efficiency and transgene expression, and to assess whether the location of the MAR in the construct had any influence on these effects, we designed a series of transposon donor constructs containing the GFP and puromycin resistance (Puro) gene, in which the MAR 1–68 or a control neutral spacer DNA sequence were inserted at different positions in the plasmid . The parWe first estimated the transposition efficiency of the various transposon constructs by assessing the percentage of GFP-expressing cells after transfection and three weeks of cultivation without antibiotic selection, so as to dilute away and eliminate non-integrated and thus non-replicating episomal plasmids. In parallel, we also assessed transposition efficiency by counting puromycin-resistant colonies as before. When using the parental Puro-GFP transposon vector, cytofluorometry analysis indicated that approximately 3% of the cells stably expressed GFP when the transposase was expressed, whereas less than 0.2% retained detectable expression from spontaneous genomic integration resulting from cellular recombination activities . The MARAntibiotic selection yielded a lower apparent transposition frequency from the parental Puro-GFP construct  early promoter. Use of the weaker promoter yielded comparable numbers of GFP-positive cells and of integrated transgenes, indicating that the transposition efficiency is not altered by transgene expression 3B. HowevWe next wished to determine whether MAR-containing transposons may be used to express therapeutic proteins using the CHO-M cell line grown in suspension culture CHO-M cells were electroporated once or twice with the single transgene MAR X-29-containing transposable vector, using a multiple gene transfer procedure Expression cassettes encoding the heavy or light chains of three therapeutic immunoglobulins  were inserted upstream of the MAR X-29 into the transposable vector instead of the puromycin resistance and GFP coding sequences. The resulting constructs were electroporated thrice with the piggyBac transposase vector into CHO-M cells. After three weeks of culture without selection, secretion of the three antibodies was quantified from the cell culture supernatants. Titers ranging from 1 to 8 µg/ml of Bevacizumab, Adalimumab and Rituximab were obtained in several transfection experiments, indicating that significant expression of these antibodies may be obtained when assessing the culture supernatants of unselected polyclonal cell populations . These lWe next assessed whether highly expressing cell clones may be obtained from the non-sorted and non-selected polyclonal populations using an imaging device for cell colony productivity. Two colonies displaying favorable size, indicative of fast cell growth, and high immunoglubulin secretion were picked from each of the three immunoglobulin-expressing cell populations. Immunoglobulin secretion by the 6 cell clones was assessed using small scale cell suspension cultures in spin tube bioreactors. The immunoglobulin-expressing clones produced antibody titers ranging between 0.55 to 1.2 g/L over the 9-day fed-batch cultures , while rWe next assessed whether transposon vectors may also be used for the metabolic engineering of CHO cells to achieve improved secretion of therapeutic proteins. We have recently shown that the expression of difficult-to-express immunoglobulins like the Infliximab antibody can be increased significantly by the expression of proteins of the secretion pathway, such as the signal peptide recognition proteins SRP9, SRP14, SRP54, the SRPRalpha and SRPRbeta components of the SRP complex receptor (SR), and/or the Translocon subunits So far, most studies involving transposable vectors have relied on antibiotic resistance-based assays, which has not allowed a clear and quantitative disentanglement of transgene copy number-linked effects from those elicited by variations of transgene expression levels. In this study, we wished to evaluate the potential benefit of adding an epigenetic regulator to a transposable vector in conditions allowing the quantitative assessment of both transposition efficiency and transgene expression. This study shows that the human MAR 1–68 can be added at a central position in the piggyBac transposon without decreasing transposition efficiency, while it’s insertion at the transposon edge may interfere with the transposase function, both in terms of transposition efficiency, and, surprisingly, expression per transgene. Inclusion of the MAR 1–68 at the edge of the transposon may cause topological constraints that would hinder the joining of the two ITR by the transposase, which would in turn reduce transgene integration by the transposase. The decrease of expression per transgene copy elicited by MAR 1–68 when inserted at the transposon edge suggests that the transposons may have integrated at genomic loci that are less favorable for expression. Thus, the MAR 1–68 may have altered the mechanism by which the transposase targets a genomic locus to integrate the transposon sequence. Interestingly, this effect appears to be specific to MAR 1–68, as inclusion of human MAR X-29 at the edge of the transposable sequence did not yield low transposition efficiency or expression. While the cause of such MAR-dependent effects remains unclear, this may result from the specific organization of DNA bending-prone sequences as well as transcription factor binding sites whose combinations and relative positions differ when comparing distinct MAR elements Interestingly, the extent of the MAR-mediated activation of transposed genes was reduced when compared to that of spontaneous plasmid integration. Furthermore, the level of expression, when normalized to transgene copies, was higher from the transposons than those obtained from the spontaneous integration of the plasmids in the absence of the transposase. This effect was observed irrespective of the size of the constructs, of the presence of the MAR or of promoter strength. This would be expected if transposition might often occur at genomic loci that are relatively permissive for expression, for instance because open chromatin structures may be more accessible to both the transposase and transcription factors. In this respect, previous studies have suggested that transposons may preferentially integrate within gene introns Further work may be required to determine why expression from plasmid vectors is more dependent on the MAR than transposon vectors. Nevertheless, our results indicate that the highest expression levels per transgene were obtained from a MAR-containing transposon when coupled to a strong promoter, and that high expression levels can be obtained from a few transposed transgene copies. Use of transposable vectors may be advantageous for the production of proteins for pharmacological use. For instance, fewer integrated transgene copies should be advantageous if high productivities can nevertheless be obtained, as documented in this study for three therapeutic antibodies, because it should decrease the probability of point mutation occurrence in one or in a subset of the transgenes, as elicited from spontaneous mutagenic events. In addition, transposase-mediated integration events may be less mutagenic than the DNA repair and recombination mechanisms involved in spontaneous plasmid integration, which can lead to incomplete or rearranged transgene copies.The high efficiency of genomic integration by the piggyBac transposon should also be favorable when the amount of target cells is limiting, for instance for the non-viral transfer of therapeutic genes in primary stem cells to generate clonal populations, with cell-based therapies or regenerative medicine as perspectives. In this context, physiological expression levels from a few transposed gene copies and the frequent occurrence of transposition events, thus obviating the need for antibiotic selection, should be of advantage, since the use of antibiotic resistance genes and/or unreliable transgene expression may raise safety concerns.Finally, transposons should also be favorable for cellular metabolic engineering, for instance to express secretion proteins and/or when multiple rounds of gene introduction are required. This is illustrated in this study by the expression of multiple proteins of the cell’s secretory pathway, where the transfection of multiple vectors and/or multiple successive transfection cycles may exhaust available antibiotic or other selection methods. Alternatively, the ability to quickly express therapeutic proteins without a need for antibiotic selection is of interest, for instance when multiple therapeutic protein candidates must be expressed for screening purposes, as significant amounts of proteins can be obtained from unselected cell populations 2–3 weeks after transfection. Overall, we thus conclude that MAR-containing transposons will be useful additions to the currently available arsenal of expression vectors.The PB transposase expression vector pCS2+U5V5PBU3 contains the PB transposase coding sequence surrounded by the 5′ and 3′ untranslated terminal regions (UTR) of the Xenopus laevis β-globin gene. This plasmid was constructed as follows: the 3′ UTR 317 bp fragment from pBSSK/SB10 (kindly provided by Dr S. Ivics) was inserted into pCS2+U5  to yield pCS2+U5U3. The PB transposase coding sequence  was synthesized by ATG:biosynthetic  and cloned in the pCS2+U5U3 backbone between the two UTRs. The PB control vector corresponds to the unmodified pCS2+U5 plasmid .R), under the control of the SV40 promoter from pRc/RSV plasmid (Invitrogen/Life Technologies), was then inserted between the two ITRs. The MAR 1–68 and MAR X-29 elements, the puromycin resistance and GFP genes used in this study were as previously described The different transposons vectors used in this study were generated by introducing the PB 235 bp 3′ and 310 bp 5′ inverted terminal repeats (ITRs), synthesized by ATG:biosynthetic , into the pBluescript SK- plasmid . Two days after the transfection, cells were transferred to several Petri dishes depending on the experiment. For analysis of unselected transfected CHO cells, cells were replated without antibiotic selection for 3 weeks and the percentage of fluorescent cells and the fluorescence intensity of GFP positive cells were determined by FACS analysis using a CyAn ADP flow cytometer (Beckman Coulter). For gene copy number analysis of unselected cells, stable GFP positive CHO cells were sorted using a FACSAriaII. For antibiotic resistant colony-counting assays, 50,000 transfected cells were seeded in 100 mm plates and selected with 5 µg/ml puromycin for 2 weeks. Then, resistant colonies were fixed and stained in 70% EtOH 0,7% Methylene Blue for 10 min, and colonies >0.5 mm in diameter were counted. For GFP expression studies, cells were selected for two weeks before GFP fluorescence FACS analysis as described above.The CHO DG44 cell line CHO-M cells were maintained in suspension culture in SFM4CHO Hyclone serum-free medium (ThermoScientific) supplemented with L-glutamine  and HT supplement  at 37°C, 5% CO2 in humidified air. Transposon donor plasmids were transferred in these cells by electroporation according to the manufacturer’s recommendations . Quantification of immunoglobulin secretion was performed from batch cultures as described previously ACATTATGCCGGACAAAGCC and GFP-Reverse: TTGTTTGGTAATGATCAGCAAGTTG primers were used to quantify the GFP gene, while primers B2M-Forward: ACCACTCTGAAGGAGCCCA and B2M-Reverse: GGAAGCTCTATCTGTGTCAA were used to amplify the Beta-2 microglobulin gene. For the amplicon generated by the B2M primers, one hit was found per CHO haploid genome after alignment to our CHO genome assembly using NCBI BLAST software. As CHO are near-diploid cells Total DNA was isolated from CHO stable cell pools following transposition assays using the DNeasy Tissue Kit  according to the manufacturer’s protocol. The copy number of genome-integrated transgenes was assessed using 6 ng of genomic DNA by quantitative PCR using the SYBR Green-Taq polymerase kit from Eurogentec Inc and ABI Prism 7700 PCR machine (Applied Biosystems). The GFP-Forward: 5 cells per ml in SFM4CHO medium (Thermo Scientific) supplemented with 8 mM L-glutamine and 1× HT supplement (both from Gibco), referred to as Complete Medium. After 4 days in culture, 2×106 cells were washed, re-suspended in PBS and incubated with a biotinylated human IgG (KPL216-1006) at a final concentration of 3 µg/ml, together with 30 µl pre-washed MyOne T1 streptavidin-coated Dynabeads (Invitrogen), on a rotary wheel for 30 minutes at room temperature. The cell and bead mix was then placed on a magnet to separate labeled cells from non-labeled cells. The beads were washed 4 times with a phosphate buffer saline (PBS) solution. After the final PBS wash, the beads and cells were re-suspended in 500 µl pre-warmed Complete Medium, transferred to a 24 well plate and incubated at 37°C with 5% CO2. After 24 h the magnetically-sorted polyclonal cells were separated from the beads and incubation was continued until the cells were of a sufficient density for expansion in 50 mL TPP spin tube bioreactors .To magnetically sort IgG-expressing cells, transfected CHO-M cells were seeded at a cell density of 3×105 cells/ml in a peptone-containing growth medium (Hyclone SFM4CHO supplemented with 8 mM glutamine) in a humidified incubator maintained at 37°C and 5% CO2, with orbital shaking at 180 rpm.Alternatively, two clones were isolated from non-sorted and non-selected populations expressing each of the three IgGs using a ClonePix device. Briefly, semi-solid media was used to immobilize single cells, and colonies secreting high amounts of IgG were picked ten days post-embedding. These cell lines were passaged every 3–4 days in spin tube bioreactors at a density of 3×105 cells per ml and grown for 6 days in 5 ml of Complete Medium in 50 ml Spin tube bioreactors when assessing polyclonal cell populations. Alternatively, shake flask cultures of clonal populations were inoculated at a density of 3×105 cells/ml into SFM4CHO media to initiate the fed batch production process. Fed batch production assays were performed with 25 ml of culture volume in 125 ml shake flasks or 5 ml in 50 ml TPP culture tubes in humidified incubators maintained at 37°C and 5% CO2 with shaking at 150 rpm (125 ml shake flask and spin tubes). The production was carried out for ten days by feeding 16%, of the initial culture volume of chemically defined concentrated feed  on days zero, three and six to eight. No glutamine and glucose feeding was applied during the culture run. The viability and viable cell density (VCD) of the culture was measured daily using a GUAVA machine (Millipore). A double sandwich ELISA assay was used to determine MAb concentrations secreted into the culture media.IgG titers were determined from cells seeded at a cell density of 1×10Figure S1Optimization of piggyBac transfection conditions in CHO cells. PB transposition activity was measured under fixed amount of the puromycin resistance gene bearing transposon plasmid (300 ng) co-transfected with increased amount of transposase plasmid. (A) Puromycin resistant colonies were stained after 2 weeks of selection. (B) Fold increase in colony number induced by the PB transposase. Values represent the means ± SD (n = 2).(TIFF)Click here for additional data file.Figure S2Models of transgene integration from transfected plasmids. (A) Model of multi-copy plasmid chromosomal integration resulting from classical stable transfection methods, resulting in a preferential head-to-tail transgene organization (TIFF)Click here for additional data file.Figure S3Effect of MAR and transposase upon integrated transgene copy number. The number of integrated GFP transgene copies was determined using qPCR, and values were normalized relative to the cellular B2M gene, using genomic DNA isolated from unselected CHO cells (A), or puromycin-resistant cells (B) generated as described in the legends to (TIF)Click here for additional data file.Figure S4Effect of MAR 1–68 on transposition efficacy and transgene expression from a weak promoter. CHO cells were transfected as described in the legend to (TIF)Click here for additional data file.Figure S5Assay of single transgene MAR-bearing transposable vectors. (A) CHO-M cells were electroporated with the depicted transposon donor constructs containing or not human MAR 1–68 or X-29 together with the piggyBac transposase expression vector. The percentage of GFP positive cells was determined from the total cell population maintained in suspension culture for 12 or 33 mean population doubling time. (B) Densitometric profiles of CHO-M electroporated with the GFP-MARX-29 transposon donor with (+PB) or without (-PB) the piggyBac transposase expression vector. Cell fluorescence was assayed after single or double transfections followed by 3 weeks of cell culture performed in the absence of selection. The horizontal bar indicates the sectors used to quantify expressing from non-expressing cells.(TIFF)Click here for additional data file.Figure S6Culture growth of cell clones producing therapeutic antibodies from transposable vectors. The viable cell densities (A) and the cell viability (B) are shown for the tube spin bioreactor runs displayed in (TIF)Click here for additional data file.


Traumatic brain injury (TBI) can result in persistent sensorimotor and cognitive deficits including long-term altered sensory processing. The few animal models of sensory cortical processing effects of TBI have been limited to examination of effects immediately after TBI and only in some layers of cortex. We have now used the rat whisker tactile system and the cortex processing whisker-derived input to provide a highly detailed description of TBI-induced long-term changes in neuronal responses across the entire columnar network in primary sensory cortex. Brain injury (n = 19) was induced using an impact acceleration method and sham controls received surgery only (n = 15). Animals were tested in a range of sensorimotor behaviour tasks prior to and up to 6 weeks post-injury when there were still significant sensorimotor behaviour deficits. At 8–10 weeks post-trauma, in terminal experiments, extracellular recordings were obtained from barrel cortex neurons in response to whisker motion, including motion that mimicked whisker motion observed in awake animals undertaking different tasks. In cortex, there were lamina-specific neuronal response alterations that appeared to reflect local circuit changes. Hyper-excitation was found only in supragranular layers involved in intra-areal processing and long-range integration, and only for stimulation with complex, naturalistic whisker motion patterns and not for stimulation with simple trapezoidal whisker motion. Thus TBI induces long-term directional changes in integrative sensory cortical layers that depend on the complexity of the incoming sensory information. The nature of these changes allow predictions as to what types of sensory processes may be affected in TBI and contribute to post-trauma sensorimotor deficits. In many cases of brain disorders, sensory processing deficits may contribute significantly to the overall morbidity of the condition Traumatic brain injury can occur from any blow to the head such as in car accidents, sporting field blows, and falls, and can produce very severe and life-long debilitating deficits in cognitive and sensorimotor function This issue on the changes in neuronal processing of sensory input that could underlie diffuse TBI-induced disturbances in sensory behaviours has been examined in the rat barrel cortex that receives input from the mystacial whiskers that allow navigation in confined and complex spaces, permit detection of objects, and underlie object discrimination and recognition, with tactile acuity that easily matches that of humans One limitation of these studies is that they were restricted to recording from layer 4 and also examined only effects in the short term (within 3 hours) after brain injury and therefore provide no information about dynamics of the full network over the long term nor the effects of the changes in excitation/inhibition balance on coding of whisker motions as used in natural behaviours. In fact this is a general limitation of the majority of studies investigating sensorimotor behaviour after diffuse TBI: they have only shown deficits over shorter time periods, have not focussed on sensory-specific morbidities, nor have they covered the dynamics of changes across the entire cortical network in a manner that can be related directly to normal sensory behaviour ad libitum food and water. Following 1 week acclimatisation, which included behaviour tests, animals underwent surgery to create diffuse traumatic brain injury (TBI) or for Sham controls. The cycle of acclimatisation, surgery, recovery and terminal electrophysiological experiments was done 5 times with 6–8 rats/cycle, allowing animals from a single cycle to be tested in terminal experiments in a short period in weeks 8–10 post-brain injury, removing any confound from age-related changes or from animals in a particular group being tested at different times post-surgery. In each cycle, littermates were randomly allocated to either TBI or Sham groups for surgical treatment.Adult male Sprague-Dawley rats  from the Alfred Medical Research and Education Precinct (AMREP) Animal Service were housed under a 12-h light/dark cycle with All experiments were conducted in accordance with the Code of Practice for the Care and Use of Animals for Scientific Purposes , and received approval from the AMREP Animal Ethics Committee and the Monash University Standing Committee on Ethics in Animal Experimentation .ad libitum. Body temperature was maintained at 37.5°C using heat pads during surgery and for the next 24 h. Sham animals underwent the same surgical preparation as TBI animals but did not receive the traumatic impact.Brain injury was created in 19 rats using the weight-drop impact acceleration method Sensorimotor and cognitive function was assessed with a variety of tests, consisting of standard tests of TBI-induced deficits  or failure to place within 5 seconds was scored as 0 The second whisker-based test is a modified version of the whisker nuisance task used to examine persistent sensory deficits post-diffuse TBI In week 7 post-surgery, the Novel Object Recognition Test (NORT) was conducted to examine exploratory behaviour, anxiety and memory function In weeks 8–10 after surgery, TBI (n = 16) and Sham (n = 14) animals were tested in terminal experiments in which extracellular recordings were obtained from the posteromedial barrel subfield cortex (barrel cortex) using previously-detailed methods Surgery A parylene-coated tungsten microelectrode  was advanced, using an electronically controlled fast-stepping microdrive, through the dura to contact the cortical surface. Contact fidelity was confirmed through high-power microscopy and audiovisual monitoring of the amplified and filtered microelectrode output The neural signal was amplified and band-pass filtered from 0.3–10 kHz and passed through a Schmitt trigger box which was used to set a voltage trigger level, approximately 1.5×>mean noise level at the recording location, for recording of cluster activity see . Spike2 Computer-controlled PW deflections were applied to obtain data, using our novel motor-controlled lever arm system At each recording location a suite of 3 trapezoids with varied onset ramp velocity  with fixed deflection amplitude of 3.6 mm, ‘was applied to characterise cluster responses, and to extract single unit waveforms using spike sorting algorithms. Then, to record responses of barrel cortex to “naturalistic” whisker motion, suites of 4 complex motion waveforms were applied. During data collection, responses from the cluster were displayed online as PSTHs and raster displays The 3 trapezoidal stimuli were generated de novo online using Spike 2 software and for on-line spike sorting, waveform templates were generated from responses to the suite of trapezoids, presented pseudo-randomly; 300–750 repetitions of each stimulus were used to obtain reliable waveforms for spike sorting. Standard Spike 2 template matching algorithms were applied to separate individual waveforms. A maximum of 6 waveforms (in most cases 3–4 waveforms) was obtained at any location. Throughout data collection the different single neuron waveforms were continuously monitored to ensure recording fidelity.The 4 complex “naturalistic” whisker deflections were played out from text files which stored stimulus characteristics. These waveforms were generated from waveforms published in studies in which whisker motion had been imaged in awake behaving rats, and were those seen (a) in whisker motion across smooth and rough surfaces These “naturalistic” complex whisker deflections were obtained from high-resolution images in the online versions of the three reports The values of the movement axis of these waveforms were converted  to distance in mm, with whisker position values normalised and scaled (without clipping the waveform) to a maximum deflection amplitude of 3.6 mm. These values were saved into a “signal” textfile of whisker position values (in mm) over time. A second ‘Stimulus Textfile’ was generated to determine how the signal textfile would be played out, including scaling factors to ensure the maximum amplitude did not exceed 3.6 mm. Spike2 software was used to open and play out the signal textfile, through the CED Power 1401 A–D converter to the motor controlling the lever arm that moved the whisker. As described before The whisker motion waveform encoded in a signal textfile was played out as a suite of motions varying only in overall amplitude. Ten stimulus amplitudes were used in each suite, starting with 0.2 mm and then continuing from 0.4–3.6 mm, in 0.4 mm steps. Each amplitude was presented 50 times, with the different amplitudes in pseudo-random order across successive presentations.The four “naturalistic” whisker deflections varied in waveform complexity. Due to the brevity of each stimulus, and the limited sample size , standard spectral waveform analyses could not be applied to classify the stimuli. An alternative method of quantifying such complex waveforms is in terms of their fractal dimensions FD; . HoweverData were collected from rotarod, beam-walk, adhesive tape removal tests, whisker evoked forepaw placing test and whisker nuisance task over a period of 6–7 weeks which included pre- and post-trauma testing periods. Rotarod data were analysed using two-way repeated measures ANOVA. To obtain % of maximum rotarod, all scores were divided by the highest score each animal received in its pre-trauma/surgery tests. Beam walk, adhesive tape removal latency, whisker nuisance task and whisker evoked forepaw placing tests were analysed using a non-parametric Mann-Whitney U test. A p value of <0.05 was considered to be statistically significant. The novel object recognition test was analysed using a one-sample t-test with a hypothetical mean of 0.5 to determine statistical significance.Clusters and single neurons were segregated into lamina by depth as Layer 2 ; Upper Layer 3 (350–500 µm); Deep Layer 3 (550–700 µm); Layer 4 (750–1000 µm); and Layer 5 (1100–1400 µm). A 50 µm buffer was used between layers to avoid allocating neurons to an incorrect layer. In practise we did not collect data from depths below 1500 µm from the cortical surface and so the Layer 5 data is likely to be almost totally from layer 5A only.For all electrophysiological recordings data were collated as firing rate (in spikes/sec) in 1 msec bins over the period from 200 msec prior to stimulus onset until 100 msec post stimulus offset. Data from the clusters was used for offline analysis to generate population PSTHs to show the pattern of population responses within a lamina. For this, data for each stimulus  from each cluster in a lamina were averaged across all presentations of that stimulus. These average PSTHs were corrected for the pre-stimulus spontaneous activity using the 200 ms pre-stimulus firing rate, also averaged across all repetitions of the stimulus. A 5-point weighted moving average was applied to smooth out any noise and the data were then averaged across all multi-units to produce a grand PSTH. These grand PSTHs were used to identify the pattern of population responses to each stimulus and then determine appropriate counting windows for quantitative analyses.velocities from the 3 test velocities used in the trapezoidal stimulus or amplitudes from the 10 test amplitudes used for each of the 4 naturalistic stimulus waveforms. We then extracted the peak firing rate, average firing rate and area under the curve for each stimulus. For these calculations, specific counting windows were established for each stimulus to encompass the maximum response over the stimulus presentation period. For the trapezoidal stimuli, a counting window from 5–50 ms after stimulus onset was used. The texture discrimination stimuli (rough and smooth) and object contact stimulus were analysed using a 5–30 ms counting window, while the free whisking stimulus was analysed using a 5–200 ms counting window.For quantitative analysis for each stimulus waveform , we used only data from single neurons deemed to be responsive to that stimulus. A cell was deemed to be responsive if there were statistically significant responses at two or more consecutive stimulus Statistical analyses were carried out for each of the firing rate and temporal measurements for each stimulus waveform. For each set of results from a specific waveform, essentially two levels of analyses were carried out. The first was an omnibus mixed-model repeated measures ANOVA, consisting of the following factors: 2 Groups×5 Layers×10 Amplitudes . When significances were seen in this global analysis, repeated-measures ANOVAs were conducted for intra-laminar comparisons between the TBI and Sham groups. For this repeated-measures analysis the following factors were used: 2 Groups×10 Amplitudes . Given this entailed a large number of within- and between-subjects comparison metrics in these repeated-measures ANOVAs, for clarity of reading, for these analyses we present only the meaning of the analyses in the Results section, with detailed metrics for each analysis presented in the Supplementary Information section. A p value of <0.05 was considered to be statistically significant. All data are reported as mean ± SEM.p<0.05), beam walk scores (p<0.05), and adhesive tape removal test of manual dexterity (p<0.05). Thereafter, TBI animals improved at different rates for the different tests. For the rotarod test, even at 6 weeks post-trauma they were significantly worse  while for the beam walk test significant deficits were present up to 6 days post-trauma , and at week 3 , with a gradual recovery such that from weeks 4 to 6 TBI animals were no longer worse than in Sham animals. For the adhesive tape removal test TBI animals improved over week 1 post-trauma, reaching a plateau 2 weeks post-trauma and thereafter showed no significant difference compared to Sham animals, consistent with previous work on effects in week 1 post-injury After trauma, TBI animals showed significant and persistent sensorimotor deficits . For thep<0.05) through to week 6 post-trauma . In a second whisker-based test, using particular components of the whisker nuisance task p<0.05), and 4 , likely due to the relatively small number of animals tested in this task, a late addition to our test battery. Finally, the novel object recognition test (NORT) conducted 7 weeks post-treatment showed no significant differences between TBI and Sham-surgery animals for all three NORT phases  over at least 3 successive stimulus amplitudes of the naturalistic stimuli and at least 2 successive trapezoid deflections. For each unit, the firing rate during the stimulus period was corrected for that unit’s spontaneous firing rate. Analysis of pre-stimulus spontaneous firing rates revealed no significant differences between groups.Electrophysiological data were obtained from all layers from 2 to 5 in TBI (n = 16) and Sham (n = 14) rats, with single cells spike-sorted from multi-neuron clusters, in response to four “naturalistic” whisker deflections and three trapezoidal deflections. A responsive unit (cluster or cell) was one with responses that were significantly greater, at PFR), and (4) temporal dispersion of the peak response, measured as the duration in the analysis window over which firing rates were ≥50% of the PFR (T1/2 PFR). For all stimuli we found nearly identical effects for the two firing rate measures (PFR and EAUC), and nearly identical effects for the two timing measures (LPFR and T1/2 PFR); hence we present data only from the PFR and the latency to the peak (LPFR).For quantitative comparisons, we used the population grand PSTHs to identify different response components to each stimulus and to set appropriate counting windows to extract four metrics from all responsive single cells: (1) peak excitatory firing rate (PFR) in defined analysis window, (2) excitatory area under the curve of firing rate (EAUC) over the entire analysis window, (3) latency to the peak  are presented in on data from each lamina. In all layers PFRon increased systematically with stimulus amplitude .As shown in The Grand PSTHs generated from all responsive multi-unit clusters to this stimulus see  there waPFR; For the timing measure LPFR;  too, anyAs noted, we also applied  a dominaThus, in summary, for both discrimination waveforms, there were significant differences between the Sham surgery and TBI animals for the peak firing rate in cells in the top two supragranular layers. In all other layers there were no differences between groups. Latency to the peak response appeared uncorrelated to the PFR itself.2 = 15.6, df = 4, p<0.01) but the direction of this difference varied with lamina; when collapsed into supragranular, granular and infra-granular laminae, there was no significant difference between the two groups, .The final naturalistic waveform we consider is that used to model the natural exploratory whisking in which rats move their whiskers freely to detect objects around them. This waveform was derived from recordings of whisker motion in head-restrained rats moving their whiskers freely in air In both groups this stimulus generated a number of complex response components see  that couPFR, from each lamina ; however, this significance was lost when the layers were collapsed into supragranular, granular and infra-granular laminae, .An important stimulus parameter affecting barrel cortex responses is velocity of whisker protraction, often studied by applying trapezoidal stimuli with varying onset-ramp velocities An analysis window of 5–50 ms from stimulus onset, set to cover the entire peak response  when analysis was restricted to only the ramp component of that stimulus. This was not due to using a narrower analysis window since significant supragranular changes in TBI were seen with similar or shorter analyses windows applied to the other three naturalistic stimuli. We explored the issue of stimulus complexity in these effects by calculating the NLD value as an index of stimulus complexity (see Methods). There was some degree of correspondence between stimulus complexity and changes in PFR but the changes could not be completely explained by stimulus complexity per se since trapezoidal stimuli, which did not reveal the supragranular hyper-excitation, had an average NLD value greater than that for the full exploratory whisking stimulus. The results suggest that NLD analysis is the most appropriate measure to quantify the stimuli in terms of complexity, and that the NLD metric can be used to classify such short-duration naturalistic stimulus waveforms and at least partially differentiates cortical neuronal response diversity.variability between samples of coarse-grained (“mesopic”) multifractal properties. It seems likely then that the latter mesopic dimensions provide a better descriptor of the differences between the four signals which might allow us to understand the differences between barrel cortex neuronal responses evoked by these signals.The Kalauzi et al. models This is the first study to describe in any detail at all, the long-term consequences of diffuse TBI across the columnar network in primary sensory cortex, and amongst a small number of studies examining diffuse TBI more than 1–2 weeks post-trauma. Our results indicate that TBI induced hyper-excitation in firing rates but only in supragranular layers of barrel cortex; consistent with our conclusion that this occurred through cortex-specific changes, there were no changes in response timing as might be expected for relayed sub-cortical effects. As discussed below, our data indicate that a likely mechanism for the hyper-excitation is loss of one form of intra-cortical inhibition, surround inhibition.Given that this is, to the best of our knowledge, the only study that has described the changes across the entire columnar network after brain injury, especially in the longer-term, and to complex stimuli, it is difficult to find parallel studies that could provide some insights into the mechanisms. Ding et al. Hall and Lifshitz +-Cl- co-transporter 2 which maintains Cl- concentrations Increased excitation is commonly seen after other cortical injuries Hyper-excitability in supragranular layers with little or no change in deeper layers may reflect a simple direct distance-dependent effect of damage from the impact trauma. Previous histological studies from our laboratory using this model Reductions in, rather than loss of, inhibition more likely account for long-term post-TBI hyper-excitability. Diffuse TBI does not typically result in overt lesions or cell death in cortex or thalamus but causes widespread damage to neuronal structure and cerebral vasculature We propose that select loss of only one form of cortical inhibition may account for the effects we report. Auditory cortical inhibition is differentiated into surround and within-field inhibition  could have revealed TBI-induced neuronal hyper-excitation that was not revealed by the trapezoidal stimuli. However, TBI-induced supragranular neuronal hyper-excitation was seen with the rough surface discrimination waveform which did not have a vibratory component; further it has been well demonstrated that vibration frequency is most likely encoded by the velocity complexity) that could explain the difference in effects to the naturalistic stimuli versus the trapezoids, and even perhaps between the naturalistic stimuli. The small number of samples (waveforms) and the absence of repeats of each sample precluded standard fractal dimension analysis but allowed use of the NLD value as a measure of stimulus complexity. The TBI-induced hyper-excitation generally occurred with stimuli with higher NLD values . Firing rates were averaged across all responsive clusters  in Sham surgery animals and in TBI animals. The first column of PSTHs is from the Sham surgery cases and the second column from the TBI cases. The boxed areas represent the analysis windows from 5–50 ms post-stimulus onset to capture the onset response (shaded box) and the window from 70–130 ms post- stimulus onset to capture the offset response (dashed box). For all columns the lamina from which data were obtained for each row is indicated to the left of the PSTHs. Cluster numbers for each lamina and group are also presented.(TIF)Click here for additional data file.Figure S2Effects of traumatic brain injury on pattern of responses to the “smooth surface discrimination” whisker motion waveform: Population Grand PSTHs to the largest stimulus waveform . Firing rates were averaged across all responsive clusters  in Sham surgery animals and in TBI animals. The first column of PSTHs is from the Sham surgery cases and the second column from the TBI cases. The boxed areas represent the analysis window from 5–30 ms post-stimulus onset to capture the onset response. Figure conventions as for (TIF)Click here for additional data file.Figure S3Effects of traumatic brain injury on pattern of responses to the “free whisking” whisker motion waveform: Population Grand PSTHs to the largest stimulus waveform . Firing rates were averaged across all responsive clusters  in Sham surgery animals and in TBI animals. The first column of PSTHs is from the Sham surgery cases and the second column from the TBI cases. The boxed areas represent the analysis windows from 5–50 ms post-stimulus onset to capture the onset response (dashed box) and the window from 5–200 ms post- stimulus onset to capture the first cycle of the stimulus (shaded box). Figure conventions as for (TIF)Click here for additional data file.Figure S4Effects of traumatic brain injury on pattern of responses to the trapezoidal whisker motion waveform: Population Grand PSTHs to the highest stimulus velocity (400 m/s). Firing rates were averaged across all responsive clusters  in Sham surgery animals and in TBI animals. The first column of PSTHs is from the Sham surgery cases and the second column from the TBI cases. The boxed areas represent the analysis window from 5–50 ms post-stimulus onset to capture the onset response. Figure conventions as for (TIF)Click here for additional data file.Table S1on) and temporal measures (LPFR) in single cells responsive to the object contact whisker motion stimulus from 5–50Results of statistical analysis of firing rate (PFRms from stimulus onset (related to). The Table lists F statistics and degrees of freedom only for all significant factors and interactions and significance values for both significant and non-significant factors and interactions, for main and interaction terms for each ANOVA type used.(DOCX)Click here for additional data file.Table S2PFR) measures in single cells responsive to the smooth surface discrimination whisker motion stimulus from 5–30Results of statistical analysis of firing rate (PFR) and temporal (Lms from stimulus onset (viz.). Table format as for (DOCX)Click here for additional data file.Table S3Results of statistical analysis of firing rate (PFR) measures in single cells responsive to the rough surface discrimination whisker motion stimulus from 5–30 ms from stimulus onset (viz.). Table format as for (DOCX)Click here for additional data file.Table S4Results of statistical analysis of Peak Excitatory Firing Rate (PFR) measure in single cells responsive to the first cycle of the free whisking motion stimulus from 5–200ms from stimulus onset (viz.). Table format as for (DOCX)Click here for additional data file.Table S5PFR) measures in single cells responsive to the onset of the free whisking motion stimulus from 5–50Results of statistical analysis of firing rate (PFR) and temporal (Lms from stimulus onset (viz.). Table format as for (DOCX)Click here for additional data file.Table S6PFR) measures in single cells responsive to the trapezoidal whisker motion stimulus from 5–50Results of statistical analysis of firing rate (PFR) and temporal (Lms from stimulus onset (viz.). Table format as for (DOCX)Click here for additional data file.Results S1Description of patterns of responses in Sham and TBI animals seen in the population Grand PSTHs, to all whisker deflection stimuli.(DOCX)Click here for additional data file.


Diseases of the human gastrointestinal (GI) tract are often accompanied by diarrhea with profound alterations in the GI microbiota termed dysbiosis. Whether dysbiosis is due to the disease itself or to the accompanying diarrhea remains elusive. With this study we characterized the net effects of osmotic diarrhea on the composition of the GI microbiota in the absence of disease.We induced osmotic diarrhea in four healthy adults by oral administration of polyethylene glycol 4000 (PEG). Stool as well as mucosa specimens were collected before, during and after diarrhea and 16S rDNA-based microbial community profiling was used to assess the microbial community structure.Firmicutes dominating the mucosa and Bacteroidetes the stools. Osmotic diarrhea decreased phylotype richness and showed a strong tendency to equalize the otherwise individualized microbiotas on the mucosa. Moreover, diarrhea led to significant relative shifts in the phyla Bacteroidetes and Firmicutes and to a relative increase in the abundance of Proteobacteria on the mucosa, a phenomenon also noted in several inflammatory and diarrheal GI diseases.Stool and mucosal microbiotas were strikingly different, with Changes in microbial community structure induced by osmotic diarrhea are profound and show similarities to changes observed in other GI diseases including IBD. These effects so must be considered when specimens from diarrheal diseases  or conditions wherein bowel preparations like PEG (i.e. specimens obtained during endoscopy) are used. The human GI tract is populated by a complex community of microorganisms that play a pivotal role in the maintenance of health and the development of disease A hallmark of many GI diseases is diarrhea, which often correlates with the severity of disease. Diarrhea is characterized by increased stool frequency, decreased stool consistency and increased stool weight. Pathophysiologic mechanisms leading to diarrhea include increased amounts of fluid in the intestinal lumen due to osmotically active substances (osmotic diarrhea), impaired absorption or increased secretion of water and electrolytes (secretory diarrhea) and accelerated intestinal transit To understand the effects of diarrhea on the composition of the GI microbiota we performed a longitudinal study wherein we induced osmotic diarrhea in four healthy adults by oral administration of polyethylene glycol 4000 (PEG). PEG is a polymer that is not reabsorbed or metabolized by intestinal bacteria. It is a pure osmotic agent that binds water in the intestinal lumen and so leads to diarrhea when administered in higher doses Four healthy adult Caucasian males  participated in this study . The subjects had had neither antibiotic therapy nor episodes of diarrhea for at least 1 year prior to the study. Stool frequency and consistency were recorded daily during the study and assessed according the Bristol stool chart The study was approved by the institutional review board of the Medical University of Graz (protocol no. 20-090 ex 08/09) and written informed consent was obtained from all subjects.DNA was extracted from stools with the QIAamp DNA Stool Mini kit and from biopsies with the QIAamp DNA Mini Kit  according to the recommended protocol. The stool homogenate was incubated in a boiling water bath for 5 min prior to DNA extraction to increase bacterial DNA yield as recommended. The variable V1–V2 region of the bacterial 16S rRNA gene was amplified with PCR using oligonucleotide primers BSF8 and BSR357 as described previously Uchimehttp://SnoWMAn.genome.tugraz.at) As the initial step the data set was de-noised using the method described by Quince et al. BiodiversityR” (V1.5) prcomp function of R. OTUs significantly changing between time points were assessed either with Metastats using default settings edgeR” (V2.14.7) using a linear model accounting for the paired nature of the data The analyses were conducted using the statistical environment R (V2.12.1) To visualize the change in OTUs’ abundance in relation to diarrhea we used a scoring system in which we assigned each OTU to a respective increasing/decreasing pattern. In this way, we calculated the mean relative abundance between the pre-diarrhea states (time-point 1 and time-point 2) of each OTU. Together with the corresponding relative abundance values for diarrhea (time-point 3) and post-diarrhea (time-point 4), a three point profile (pre-diarrhea – diarrhea – post-diarrhea) of each OTU could be drawn. Only OTUs experiencing an abundance change of at least 0.05% in relation to the respective sample were included. Subsequently, a scoring system was introduced that assigned values of −1 , +1  or 0 (relative abundance change<±0.05%) to the (two) slopes of this profile. The score for the first slope was multiplied by 3 and added to the score of the second slope, yielding a specific overall score for each OTU that related to one of the nine possible profile patterns. For mucosa samples, which were only represented by pre-diarrhea (time-point 2) and diarrhea (time-point 3) states, three 2-point profiles were generated in a similar fashion. Finally, OTUs were assigned to their respective reaction pattern and these associations were visualized with Cytoscape Sequence data generated for this work can be accessed via the EBI short read archive (EBI SRA) under the accession number ERP002098.Bacteroidetes (52.6%), Firmicutes (43.1%), Proteobacteria (4%) and Actinobacteria (0.2%) After denoising and filtering the data set for chimeras and contaminant (human) sequences, 452,363 high-quality 16S rDNA sequences with an average length of 246 bp (range 230–277 bp) remained, yielding an average of 20,562 sequences per sample . The RDPBacteroidetes dominated (69.5±5.8%) followed by Firmicutes (22.1±4.7%), whereas on the mucosa Firmicutes (75.2±13.7%) were more abundant than Bacteroidetes (17.8±12.7%) . When the representation of phyla was compared between matched stool and mucosa samples  and p-values were corrected for multiple comparisons, Firmicutes (adjusted P = 0.001), Proteobacteria (adusted P = 0.027), Actinobacteria (adjusted P<0.001) and Cyanobacteria (adjusted P<0.001) were more abundant on the mucosa and Bacteriodes more abundant in stools (adjusted P = 0.016). Although we noted a trend towards increased microbial richness on the mucosa compared to stools as indicated by the rarefaction analysis . Microbial diversity and evenness, both measures of the uniformity of the phylotype assembly, also showed no statistical difference between matched stool and mucosa samples (We noted a strikingly different phylum distribution between stool and mucosa samples. In stools 8±12.7%) . Proteobanalysis , richnes samples .P≤0.0077, Student’s t-test) as shown by the principal component analysis  if matched stool and mucosa samples were analyzed by PCA, which clearly separated the two habitats irrespective of the origin from different individuals  resembling the recently published enterotype 1, in one  by Prevotella resembling enterotype 2 Weisella, Leuconostoc, Lactococcus), which were rarely detected or completely absent in stool specimens from the same person, underscoring the difference in microbial habitat composition . Both were also considered stable phylotypes .The most abundant phylotypes across all stool specimens were dominated by position . InteresP = 0.0295, paired t-test), further evidenced by decreased Chao1 and abundance-based coverage (ACE) richness estimators comparing time-point 2 with time-point 3 . Phylotype diversity and evenness showed no significant difference between pre-diarrhea and diarrhea samples, either in stools or on the mucosa . Diarrhea-state mucosal communities clustered together in the PCA, indicating an equalization of the otherwise individualized microbiotas (The administration of PEG increased stool frequency (6.0±1.5 vs. 1.2±0.6 bowel movements/day) and decreased stool consistency (stool type: 6.7±0.6 vs. 3.0±0.9) in all 4 individuals . The effe mucosa . PCA clerobiotas . Diarrherobiotas .P = 0.042) an overall reduced species richness persisted during the one week interval after PEG administration (The capacity of stool microbiotas to reconstitute was assessed by comparing samples from diarrhea (time-point 3) and post-diarrhea (time-point 4). Although species richness increased significantly towards time-point 4 in stools (stration .Lachnospiriaceae), while there was none in the mucosa samples. In stool samples the stable phylotype with the highest abundance was represented by Bacteroides vulgatus , but only in one individual , which also represented top abundant phylotypes on the mucosa as mentioned above  and the life-style of the respective microbes (adherent vs. living in suspension), certain phylotypes should experience a more pronounced abundance change compared to others. Thus we assessed the coefficient of variation (CV) of the relative abundances of phylotypes between time-point 2 and time-point 3 samples. A CV of ≤10% was chosen as threshold and only phylotypes prevalent with at least 10 reads per individual were considered. This analysis revealed that only a small fraction of phylotypes exhibited stable behavior and the proportion of these so-called “stable” phylotypes differed greatly between subjects . The majdividual . In the ed above . Severaled above . In geneylotypes . The finRikenellaceae , Alistipes and Holdemania  showed a significant relative decrease in response to diarrhea in stools  and Alistipes  also showed a significant relative decrease in response to diarrhea  on the mucosa during diarrhea.We next looked for phylotypes showing a significant relative abundance change in response to diarrhea by comparing time-point 2 with time-point 3 samples. In stools we also assessed significantly changing phylotypes involved in reconstitution by comparing time-point 3 with time-point 4 samples. We initially performed this analysis at the levels of phylogenetic ranks from phylum down to genus. After testing for multiple comparisons only n stools . No signn stools . In the diarrhea . InteresMetastats and edgeR. A not too stringent significance threshold was used in these analyses (P<0.05) to account for the relatively small sample size. The third approach involved a scoring system with graphical data visualization (denoted Viz), wherein the abundance change of phylotypes (increasing and decreasing in response to diarrhea) was scored and presented within association networks created with Cytoscape.This approach revealed only a few significantly changing taxa. It is now evident that the human GI microbiota is highly individualized Metastats identified 72 significantly changing OTUs and edgeR 20 OTUs (Viz identified 299 OTUs correlated with a respective reaction pattern (abundance change threshold ≥±0.05%) representing 9.78% of OTUs found in stool specimens. If Viz analysis was narrowed down to phylotypes showing a respective association pattern in at least 2 individuals, 61 phylotypes were evident  were reconfirmed by Metastats and/or edgeR  experienced a relative increase in abundance due to diarrhea, which was mirrored by a simultaneous decrease of these taxa in the mucosa specimens.In stool samples  20 OTUs , S12. Vi evident . To that evident  Out of tor edgeR , Fig. S2Metastats identified 87 significantly changing OTUs and edgeR 79 OTUs (Viz identified 232 OTUs correlated with a respective reaction pattern (abundance change threshold>±0.05%), representing a fraction of 7.59% of OTUs found in mucosa specimens. If Viz analysis was narrowed down to phylotypes showing a respective association pattern in at least in 2 individuals, 64 phylotypes were represented , was detected by all three methods simultaneously; 46 OTUs were identified at least by two methods simultaneously (Table. 3). Community variation was readily captured by Viz; 36 out of 64 Viz-identified phylotypes (56.3%) were reconfirmed by Metastats and/or edgeR  represented Proteobacteria (Table. 3), among them several opportunistic pathogens including pseudomonads  or the ε-proteobacterial taxon Arcobacter (e.g. OTU_596). There was a significant association of Proteobacteria with the increasing abundance pattern in Viz  and a significant association of Bacteroidetes with the decreasing pattern . As mentioned above several OTUs matching to Faecalibacterium including F. prausnitzii (e.g. OTU_206) experienced a relative abundance decrease in mucosal specimens . Both taxons are exopolysaccharide (dextran) producers and show a strong adhesion capacity, e.g. to Caco-2 cells, which might explain their preferential colonization of the mucosal habitat and their investigation regarding their potential as probiotics We used 16S rDNA-based community profiling to assess the influence of osmotic diarrhea on the composition of the human colonic microbiota. Our longitudinal study with simultaneously sampled stool and mucosa specimens enabled us to compare microbiota changes within and between individuals. We noted strikingly different community structures between stool and mucosa samples wherein Firmicutes and Bacteroidetes dominate C. difficile colitis, viral enterocolitis, IBD and IBS per se does not necessarily reflect or lead to pathology but is in turn a consequence of the diarrhea prevalent in many GI diseases.The human GI microbiota shows a high degree of inter-individual variation at higher phylogenetic levels despite a uniform community structure at lower levels where the phyla Metastats and edgeR) and a scoring system with graphical representation of the results (Viz). These analyses revealed several significantly changing phylotypes but showed reduced congruence between methods. Interestingly, the majority of phylotypes detected with Viz  were confirmed by at least one biostatistical method showing the usefulness of the scoring method. It is important to note that all three methods identified several low abundant significantly changing taxa . But reliable detection of these low abundant taxa is highly dependent on the sampling effort (sequencing depth), which can hardly reach completeness given the large number of microbes (about 1013–1014) colonizing our gut Microbial communities are complex adaptive systems, in which patterns at higher levels emerge from localized interactions and selection processes acting at lower levels Bacteroidetes and Firmicutes experiencing a relative increase or decrease in stools in response to diarrhea. On the mucosa Bacteroidetes showed a significant association with decreasing relative abundance. It is noteworthy that we observed a significantly increased fraction of Proteobacteria experiencing a rise in relative abundance in the mucosa specimens due to diarrhea. Among them were several opportunistic pathogens including pseudomonads like Pseudomonas and Acinetobacter  as well as the ε-proteobacterial taxon Arcobacter (e.g. OTU_596). Several lactic-acid bacteria (e.g. Lactococcus) also increased on the mucosa during diarrhea, and may therefore represent interesting candidates for probiotics in the setting of diarrheal disease Faecalibacterium including F. prausnitzii (e.g. OTU_206) in stools, which was mirrored by a simultaneous decrease in the mucosa specimens. This observation warrants further investigation since this anti-inflammatory GI bacterium is reported to be decreased in IBD To overcome the incongruence of the applied methods, we narrowed the findings down to phylotypes that were detected by at least two different methods simultaneously. In this way, we identified several Proteobacteria increase in response to diarrhea has been reported in several diarrheal and inflammatory GI diseases including IBD Proteobacteria are usually considered to be generalists able to colonize various habitats with diverse resources. For example we found that OTU_1341 matching to Pseudomonas putida significantly increased due to diarrhea; this pathogen shows genomic adaptation to diverse environments but can also cause severe diseases in humans Bacteroidetes and Firmicutes in our study, it is reasonable to speculate that Proteobacteria can occupy and repopulate these depleted niches more efficiently. It so seems that diarrhea per se, irrespective of its etiology, can select for this special community type with increased Proteobacteria. It is therefore important to note that these changes may not be specific for diseases like IBD but may represent an epiphenomenon of the wash-out effect due to diarrhea. Moreover, the efficient colonization capacity of Proteobacteria might explain the effectiveness of strains like E. coli Nissle 1917 used for the therapy of IBD The finding that Capturing the true microbial representation within a sample by cultivation-independent techniques is hampered by various technical challenges. Specimen handling, DNA extraction, PCR amplification and sequencing altogether are causes of bias Proteobacteria relatively increase in response to diarrhea on the mucosa is suggestive of a basic principle of the community in this niche regardless of the cause of diarrhea. When the mucosa is severely affected as in IBD, nutrients like iron derived from blood are available in excess for these efficient colonizers Viz) is a valuable tool; since it readily illustrates the reaction of the microbiota as a whole, patterns can be caught visually by the investigator.Our longitudinal study has revealed several important findings regarding the human GI microbiota and its response to diarrhea. (I) We found that stools and the mucosa represent strikingly different habitats with a different community structure and a different response to stressors like diarrhea. For this reason, studies investigating changes in the GI microbiota in association with specific diseases need to consider that the fecal microbiota does not readily reflect the mucosal community. (II) The finding that In summary, our study is proof of the principle that manipulation of basic functions of the human GI tract enables the detection of relevant microbial community changes and highlights the importance of such studies investigating basic (patho-)physiological effects on the GI microbiota.Figure S1Rarefaction analysis of pooled stools samples from all 4 time-points. A reduced richness is seen during diarrhea (T3) and a sustained reduced diversity is evident one week after diarrhea (T4). The dotted line indicates ± SEM.(PNG)Click here for additional data file.Figure S2Significantly changing stool phylotypes visualized with an association network. This supplemental figure corresponds to (PNG)Click here for additional data file.Figure S3Significantly changing mucosa phylotypes visualized with an association network. This supplemental figure corresponds to (PNG)Click here for additional data file.Table S1Oligonucleotide primers used in this study.(DOCX)Click here for additional data file.Table S2Read and OTU numbers.(XLSX)Click here for additional data file.Table S3Richness, diversity and evenness.(XLS)Click here for additional data file.Table S4Most abundant stool phylotypes.(DOCX)Click here for additional data file.Table S5Most abundant mucosal phylotypes.(DOCX)Click here for additional data file.Table S6Effect of PEG on stool frequency and stool consistency in study subjects.(DOCX)Click here for additional data file.Table S7Stable phylotypes.(XLS)Click here for additional data file.Table S8Significantly changing taxa between pre-diarrhea and diarrhea stool samples.(DOCX)Click here for additional data file.Table S9Significantly changing taxa between diarrhea and post-diarrhea stool samples.(DOCX)Click here for additional data file.Table S10Significantly changing taxa between pre-diarrhea and diarrhea mucosa samples.(DOCX)Click here for additional data file.Table S11Significantly changing stool phylotypes identified by Metastats.(XLSX)Click here for additional data file.Table S12Significantly changing stool phylotypes identified by edgeR.(XLS)Click here for additional data file.Table S13Changing stool phylotypes identified by Viz.(XLSX)Click here for additional data file.Table S14Significantly changing mucosal phylotypes identified by Metastats.(XLSX)Click here for additional data file.Table S15Significantly changing mucosal phylotypes identified by edgeR.(XLS)Click here for additional data file.Table S16Changing mucosal phylotypes identified by Viz.(XLSX)Click here for additional data file.