SPO11 were identified and characterized genetically and cytologically. Recombination, spore viability and synaptonemal complex (SC) formation were decreased to varying extents in these mutants. Arrest by ndt80 restored these events in two severe hypomorphic mutants, suggesting that ndt80-arrested nuclei are capable of extended DSB activity. While crossing-over, spore viability and synaptonemal complex (SC) formation defects correlated, the extent of such defects was not predictive of the level of heteroallelic gene conversions (prototrophs) exhibited by each mutant. High throughput sequencing of tetrads from spo11 hypomorphs revealed that gene conversion tracts associated with COs are significantly longer and gene conversion tracts unassociated with COs are significantly shorter than in wild type. By modeling the extent of these tract changes, we could account for the discrepancy in genetic measurements of prototrophy and crossover association. These findings provide an explanation for the unexpectedly low prototroph levels exhibited by spo11 hypomorphs and have important implications for genetic studies that assume an unbiased recovery of prototrophs, such as measurements of CO homeostasis. Our genetic and physical data support previous observations of DSB-limited meioses, in which COs are disproportionally maintained over NCOs (CO homeostasis).Spo11 is the topoisomerase-like enzyme responsible for the induction of the meiosis-specific double strand breaks (DSBs), which initiates the recombination events responsible for proper chromosome segregation. Nineteen PCR-induced alleles of  SPO11 alleles in yeast with a wide range of Spo11 activity. Genetic analysis and high throughput sequencing of tetrads from these mutants has revealed unexpected features of meiotic recombination. First, Spo11 DSBs likely continue to form throughout a pachytene arrest in cells compromised for Spo11 activity. Second, the number of recombination initiation events in a given meiosis influences the repair outcome of those events. In addition, our results provide support for crossover homeostasis – a phenomenon in which crossovers are disproportionately maintained over other types of repair in the face of a decrease in DSBs.Most eukaryotes depend on the meiotic division to segregate each pair of chromosomes properly into their gametes. Chromosome segregation mistakes happening during meiosis are responsible for most miscarriages as well as many diseases such as Down's and Kleinfelter's syndromes in humans. Proper chromosome segregation during meiosis depends on efficient and regulated recombination events that link homologous chromosomes prior to the first meiotic division. These linkages are initiated at double-stranded breaks (DSBs) in chromosomal DNA by Spo11 and associated proteins. We isolated a valuable new set of  An important function of meiosis is to precisely segregate one copy of each chromosome into cells that become gametes. This accurate division is accomplished by presenting the meiosis I spindle with homolog pairs that have been linked by crossovers (COs), so that partner chromosomes can segregate from each other. Chromosomes that fail to sustain a CO are at risk of undergoing nondisjunction, and may produce aneuploid gametes that are usually inviable. A single CO can be sufficient for proper segregation. However, those COs that occur too close or too far from the centromere can also be detrimental Meiotic DSBs formed by Spo11 are regarded as the major initiating events for CO and non-crossover (NCO) recombination in all organisms studied to date spo11 alleles has been previously used to assess the consequences of reduced numbers of DSBs on CO distribution and frequency Efficient interhomolog repair requires that the two homologs pair, at least locally, at DSBs. In yeast and mice, Spo11-initiated recombination has been shown to be essential for chromosomes to find their homologous partners and establish stable pairing In budding yeast meiosis, most COs result from resolution of a double Holliday junction, while NCOs arise predominantly through synthesis-dependent strand annealing (SDSA) ARG4 region was used to substantiate the existence of CO homeostasis spo11 alleles generated prototrophs with increasingly higher levels of CO association , suggesting that, as DSBs become scarce, a given recombination event is more likely to be repaired as a CO. A second way to define CO homeostasis was described The analysis of flanking marker exchange among prototrophs in the It is noteworthy that measurement of GC tract lengths is constrained by the density of heterozygous markers. Two studies in yeast spo11 alleles and characterize them using genetics and sequencing to evaluate the relationship between recombination initiation and recombination outcomes. Historically, prototroph assays have been used as a genetic measure for DSB levels. We find, that especially for meioses with severely reduced Spo11 activity, prototroph frequencies critically underestimate DSB formation. Our findings indicate that a reduction in DSB activity influences detectability of recombination events due to alterations in the lengths of GC tracts. The extent and direction of tract length change depends on whether the event results in a CO or NCO.Since Spo11 is the enzyme that catalyzes DSB formation, the identification of additional alleles can be a valuable tool for deciphering the role of DSB levels in various aspects of meiosis. Here we isolate nineteen new spo11 alleles were isolated by screening transformants carrying PCR-derived mutant SPO11 sequences for defects in gene conversions and spore viability  to 1.6 fold reduced (for spo11-118), at the most restrictive temperature. Interestingly, the vast majority of mutants are cold sensitive; for example, the spo11-245 mutant exhibits 55% of the wild-type levels of COs at 31.5°C, but only 3.8% of the wild-type level at 18°C.A wild-type diploid and twenty mutants  nt, Zip1 . The synsynapsis .spo11 hypomorphs, we measured SC formation in an ndt80 background. Ndt80 promotes progression beyond the pachytene stage of meiosis, thus SPO11 ndt80 cells arrest with fully synapsed chromosomes spo11 mutants only produced rare nuclei with partial SCs, in the ndt80 background such mutants displayed up to 96% of meiotic chromosome spreads with SC . To further examine this apparent rescue of the spo11 phenotype, recombination levels were measured by scoring Arg prototroph formation after 48 hours of ndt80-arrest by a return to growth assay. While previous work reported small increases in heteroallelic prototrophy levels in ndt80- and cdc28-arrested cells ndt80 strain did not increase Arg prototrophy levels compared to WT  levels.In order to score synapsis in a uniformly arrested population for several severely defective  with SC . This nded to WT . Howeverectively  comparedspo11 hypomorphs arrested at late pachytene. To explore this question we used an estrogen-inducible NDT80 allele spo11 hypomorphs after 48 hours of ndt80 arrest produced a large increase in spore viability . Although CO values appeared to be somewhat temperature sensitive  fell at a much greater rate especially in alleles with severely compromised Spo11 activity than other indicators of recombination ability . Second, although flanking marker exchange among Arg and Leu prototrophs increased as expected in spo11 alleles with moderate defects (presumably due to CO homeostasis), in the most severe alleles, CO association surprisingly decreased compared to less severe mutants. Previous work using moderate spo11 alleles noticed a weakening of CO homeostasis as DSB activity decreased and proposed that CO homeostasis was strongest in cells with relatively high levels of DSBs Our genetic experiments reveal two unexpected results. First, heteroallelic gene conversion levels  to a clinical isolate (YJM789). The parental strains differ from each other at ∼55,000 locations (single-nucleotide polymorphisms (SNPs)) allowing most interhomolog recombination events to be detected To better understand the effects of spo11 hypomorphs  were subjected to high-throughput, multiplexed sequencing. The data were compared to sequenced data from three wild-type tetrads sporulated at 30°C of which two were reported previously spo11-217 mutant had an average of 80 COs .Spores from five tetrads derived from f 80 COs ; these wf 55 COs ; these wSPO11 hypomorphic tetrads revealed a similar proportion of recombination types as observed in WT. The sole exception is a disproportionate reduction of NCOs . On these 5 E0 chromosomes no other events (NCO's) were observed.CO interference is the nonrandom spacing of COs that is a feature of the normal distribution of COs but not NCOs. Through sequencing analysis we obtained the positions of COs genome-wide and we then examined interference by fitting a gamma distribution to intercrossover distances Successful detection of NCOs is subject to the density of markers as well as tract length . As shown in spo11 hypomorphs, we inspected all CO and NCO events for regions of gene conversions, i.e., regions of 3∶1 or 1∶3 segregation of markers flanked by regions of 2∶2 segregation. The distance between the last marker showing 3∶1 segregation and the closest marker showing 2∶2 segregation is highly variable due to the differences in the density of markers within different regions along the chromosomes, leaving the actual tract length ambiguous. For example, a 3∶1 tract that spans only 1 kb may have the next 2∶2 markers at 10 kb on one side and 1 kb on the other. Using the common midpoint method, this tract would be scored as 6.5 kb  in length. Even a few of these might skew our tract length analysis.Gene conversion tracts result from the repair of heteroduplex or double-stranded gaps formed during DSB repair. In order to assess gene conversion tract lengths in In order to better define tract lengths, we developed an algorithm, called Tract-Seq, that estimates tract length using a Markov model for tract growth combined with Monte Carlo simulations . Figure spo11 mutants was underestimated by sequencing analysis. This could occur if the decrease in NCOs is not an actual decrease in the number of NCOs, but a decrease in the ability to detect NCOs given their shorter length. To address this issue, we calculated how many NCOs would be missed due to detection issues  . Moreovespo11 hypomorphic alleles, encompassing a wide range of activity, revealed an unanticipated relationship between reciprocal recombination and gene conversion. Although the various spo11 mutants displayed crossing over, SC and spore viability phenotypes that correlated well together, prototroph frequencies were far more influenced by the severity of the allele. This was an unexpected observation, since prototroph frequencies have commonly been used as a metric for DSB levels  produced longer resected tracts and generated fewer prototrophs than expected, and this phenomenon was apparently due to reduced levels of DSBs in the cell (and not synapsis defects) Tract lengths associated with COs become longer as Spo11 activity declines. Longer tracts may be due to an increase in branch migration and resection In contrast to GC tracts associated with COs, NCO tract lengths are shorter in cells with diminished Spo11 activity. Most NCOs are thought to occur by a different mechanism than COs which may help to explain this altered outcome. While COs go through a double Holliday junction intermediate, NCOs are thought, for the most part, to undergo a single strand invasion or SDSA  Our data raise important considerations regarding the characterization of CO homeostasis.spo11 hypomorphic tetrads revealed an overall reduction in recombination events, with a stronger reduction in NCOs, supporting the notion of CO homeostasis. However, since NCO tracts in strains with limiting DSBs are shorter, these data may reflect an inability to detect NCOs due to their lesser likelihood to span a heterologous SNP. We have estimated the loss of NCOs in the mutants by positioning tracts on the genome taking into account the actual SNP density map. In the case of our most severe hypothetical mutant (3CO) up to 16% of the NCOs become undetectable yet this apparent loss of NCOs only marginally affects measures of CO homeostasis. An alternative explanation for the reduction of NCOs, particularly in severe mutants where homolog pairing is severely compromised, may be that some DSBs fail to find their homologous partner and are instead repaired using the sister chromatid First, sequencing of Second, the assay used to measure CO homeostasis, flanking marker exchange of prototrophs, assumes that a tract emanating from a CO or an NCO would have the same probability of forming a prototroph. However, since tract lengths change in unexpected ways in both NCOs and COs, and thus alter their abilities to form prototrophs, apparent flanking marker exchange cannot be assumed to be equal, particularly in severe hypomorphs. Note that different pairs of heteroalleles and different loci will elicit unique outputs.spo11-HA mutant which has little impact on DSB levels. The authors argued that tract-length alterations might obscure NCO/CO ratios. Consistent with this, if we apply our observed tract length changes to the GFP alleles, we would expect a decrease of GFP+ recombinants associated with COs and an increase in GFP+ recombinants unassociated with a CO, since the heteroalleles are so close in this assay. So although our measurements of tract length in the HI mutants may not be significant, it seems reasonable to suggest that tract lengths are changed in modestly defective spo11 alleles in both budding and fission yeast (see above).Using a novel color system to study CO homeostasis in tetrads, Thacker et al. Consistent with the operation of CO homeostasis, we were only able to recapitulate the CO/NCO genetic data when applying the experimentally observed changes in numbers of CO and NCOs. Thus our data support the accumulating evidence that as Spo11 activity decreases, the fraction of recombination events that become COs increases.spo11 alleles can be rescued for SC formation, recombination and spore viability by the ndt80 mutant suggests that holding cells in prophase allows further DSB formation. This notion, that DSB formation may continue in cells held at mid prophase, has been suggested previously Our observation that two severe spo11 hypomorphs, but only minimally in WT? Two scenarios seem likely. In the first, DSBs are unregulated , but the repair outcome is dependent on the state of synapsis. In synapsed chromatin, the repair would favor the sister (SC is inhibitory to interhomolog recombination) and in unsynapsed chromatin, interhomolog repair would be favored. For poorly synapsed mutants, Ndt80 arrest would result in a disproportionate increase in observable recombination (and consequently increased synapsis). This model, where stably paired and/or synapsed chromatin is protected in cis from additional interhomolog repair, has been previously suggested to account for observations in worms If continued DSB activity is the result of Ndt80 arrest, then why is the genetic consequence strongly observed in certain SPO11 were generated by a degenerate PCR based method. First, the endogenous SPO11 gene from our strain background (BR1919-8B) was cloned and sequenced, and it was found to encode six altered amino acid changes compared to that reported for S288C (SGD), although it had the identical amino acid sequence to SK1, another strain often used to study meiosis. The sequence of the SPO11 gene contains a string of 12 As which can corrupt the integrity of its sequence during PCR amplification. To alleviate this problem, two As in the middle of the run were silently substituted with Gs . A centromere plasmid containing this functionally wild-type SPO11 gene and URA3 (pRS316:SPO11) was subjected to degenerate PCR amplification (GeneMorphII EZClone Domain Mutagenesis kit from Stratagene). Three independently mutagenized plasmid libraries were prepared and transformed into a spo11-null diploid yeast strain (BR4590) for screening  were incorporated into the diploid yeast strain used for the screen  were chosen for plasmid retrieval, sequencing and retesting by retransformation into BR4590. The mutations were distributed throughout the gene . Six mutSPO11::KAN (or SPO11::HYG or SPO11::NAT) allele to monitor the unmarked mutants. All strains for subsequent analysis are isogenic to BR1919-8B spo11-m derivatives The sequenced alleles were subcloned into integrating vectors (pRS306) so that they could be transformed stably into yeast by pop in/pop out and studied as homozygotes. Crosses to generate the various strains utilized a marked For nineteen of the new mutants and one previously described D290A , argininspo11-32, 179 and 217) and WT, LEU2 heteroalleles were added to the strains to measure prototrophs at a second locus. The leu2-3,112 allele already exists in the strain background. To create a second allele, a haploid was first transformed to Leu+ and subsequently transformed to leu2-cla by pop-in pop-out transformation (R477: pBR322 with EcoRI/XhoI fragment of LEU2 where the ClaI site of LEU2 was filled in with Klenow). HIS4 and iHYG flank the LEU2 gene.In a subset of mutants . Zygotes were isolated and sporulated at various temperatures. Tetrads were used from the spo11-217 strain from dissections at 31.5°C  and 24°C  and from the spo11-32 diploid, tetrads were used from dissections at 30°C . Wild-type hybrid strains were examined for temperature effects by sporulation at 22°C, 26°C and 30°C. Wild-type sequences are stored at the National Center for Biotechnology Information Sequence Read Archive (Bioproject accession number SRP028549). Output files from Recombine, CrossOver and TractSeq are available from the Dryad Digital Depository: http://doi.org/10.5061/dryad.53t4c.Strains for the sequence analysis were heterozygous for the THR1  and iTRP1  were scored for nonparental segregation among Arg prototrophs. Since the most frequently converted allele is cis to the Trp+ marker, most of the Arg+ spores are Trp+ and the reciprocal recombinants are Thr−. The number of Trp+ Thr− recombinants were doubled to account for the inability to see the reciprocal event.The fraction of Arg prototrophs resulting from a CO was determined from analysis of random dyad spores. Flanking markers, LEU2 heteroalleles and using the hygromycin resistance marker at CEN3 and the distal marker, HIS4 as flanking markers  A similar assay for CO association was carried out on chromosome 3, utilizing  markers . The conTHR4 region) prepared from random priming kit  and analyzed on a Storm phosphorimager . The “fraction recombinant bands” was estimated by summing twice the intensity of the trimer band plus the dimer band over the total intensity of the three bands. The averages of five experiments are presented. For the DSB analysis, plugs were made, ran, and hybridized as above, but from sae2Δ versions of the mutants. Three gels were averaged.Plugs were prepared from meiotic cultures and subjected to CHEF gel analysis spo11 mutants often form an aggregate of Zip1 and other proteins called a polycomplex (PC). In our strain background WT does not normally form PCs. SC was scored among Red1 positive nuclei as follows: One or no Zip1 lines (the PC can appear linear) is “no SC”; Two or more Zip1 lines but fewer than complete SC is “some SC”; and Zip1 lines encompassing the entire nuclear region is “full SC”. Raw data is presented in Meiotic chromosomes were spread according to Rockmill DNA from four-spore viable tetrads was purified and processed for Illumina high-throughput sequencing. Illumina sequencing libraries were generated using adapters for multiplexing, as described A pillar of our analysis rests on a stringent and accurate estimation of gene conversion tracts for CO's and NCO's among various tetrads. Again the ReCombine package was employed, with a few modifications. First, we examined marker calls consisting of SNPs and indels to ensure the use of high-quality heterologies and to remove markers that might be misannotated and thus assigned to the wrong parent genome. A “confusion matrix” was created by comparing quality scores against S96 and YJM789 genomes from sequenced S96 and YJM789 parental strains, an important metric during genotype calling. For example, from a sequenced S96 parent, if a SNP had a higher quality score for YJM789 than S96 or equal scores, this heterology would be classified incorrectly as an YJM SNP. This ambiguity would lead to false positives and incorrectly called events and tracts. The estimated error rate was 0.3% for SNPs and 29% for indels after a first-pass analysis; these markers were excluded. Nevertheless, some single marker events encompassed an indel with mixed reads that passed our first-pass thresholds. Sanger sequencing of genomic DNA from spores failed to validate 13 out of 14 such events. We limited our analysis to SNP marker calls given the higher genotyping errors found in indels.Second, marker calls were made on a tetrad basis and on individual spores to increase the precision of tract length predictions. The ReCombine package determines events and tracts considering all four spores Tract length boundaries were predicted using the individual spore procedure described above. The minimal tract length was defined by markers that are certain to be part of the gene conversion event, while the maximal tract length was defined by the next 2∶2 segregating flanking markers, before which the gene conversion tract must end. The difference between the maximal and minimal tract lengths is often large, leaving the actual tract length ambiguous. Rather than using a commonly used measure, such as the midpoint, we have developed an algorithm to better estimate the tract lengths, taking into account biologically relevant information such as enzymatic processivity and marker distribution asymmetry . ProcessFor events that span a single marker, a minimal interval cannot be determined with this method. This is often the case in regions with low marker density. As an example, a maximal interval might be 20 kb while a minimal interval of 1 bp. In such cases, using the maximum likelihood estimation from geometric distribution with processivity “p” described above to fine-tune estimated tract lengths, intervals of similar length would be generated. Since these point events are common (∼15%), it would result in biases during distribution fitting. To circumvent this problem, we made an estimation of tract length for tracts defined by a single SNP. From the linear relationship between maximal tract lengths and tract lengths defined by multiple SNPs, we determine an approximation for the tract length for a single SNP tract based on its maximal tract length.SPO11 genotypes were pooled). Gene conversion tract lengths can be described by a log-normal distribution http://mcmc-jags.sourceforge.net/) to determine the mean and standard deviation of log normal distributions. We tested the goodness of fit using Kolmogorov-Smirnov tests and could not reject any fitted curves from tract length data points . Significance in the differences of the means was tested using re-sampling by comparing actual means along with the corresponding error on the means obtained from MCMC iterations (sdmean), correcting these sdmean for sample size differences (i.e. different numbers of tract lengths (data points) used in the distribution fitting process).To ensure a better overall fit, tract lengths from COs and single tract NCOs were grouped by their levels of Spo11 activity: WT, HI and LO. Tracts from complex events, such as NCOs on two chromatids and NCOs associated with a CO, display longer tract lengths than regular COs and NCOs, and these types were treated separately . Number of COs with tracts was estimated at 71% from pooled WT, HI and LO tetrads. Assuming a linear decrease in the proportion of NCOs as Spo11 activity diminishes (CO homeostasis), the number of total NCO's was estimated at 5.5, 1.2 and 0.3 for mutants with 30, 10 and 3 CO's respectively, using a linear regression for the fraction of CO's in total events from tetrad sequencing data. To determine the fraction of “complex events” , the average proportion across WT, HI and LO was used. Complex NCO events are 14% of total NCO events and each event consists of two distinct tracts. Similarly, 7% of total CO's include a conversion tract on a third chromatid. In analyses involving the absence of homeostasis, the number of NCO events was kept constant at the same fraction of total events as in WT.ARG4 from in silico analysis did not follow the trend seen in genetic assays due to the overproduction of prototrophs from CO tracts, we performed non-linear regressions to increase the means of CO curves and obtained overall better fit compared to a simple linear regression. Specifically, the following non-linear models were used during extrapolation: lm(mean ∼ √#CO), lm(mean ∼ log(#CO)) and lm(mean ∼ 1/#CO). The latter one provided the best fit to genetic data for CO association and prototroph formation frequency at ARG4.Means and standard deviations of log normal CO and NCO distributions for simulated mutants were first inferred using linear models lm(mean ∼ #CO) and lm(sd ∼ #CO). Given that the CO association at Figure S1spo11 alleles. A) The alignment of SPO11 to Methanococcus jannaschii topoisomerase VI subunit A  was used to locate the spo11 alleles into known features of the topoisomerase VI subunit A crystal structure. Molecular graphics and analyses were performed with the UCSF Chimera package (http://www.cgl.ucsf.edu/chimera). The model (TopVI_map100_labels.py) is found at Dryad Digital Depository: http://dx.doi.org/10.5061/dryad.[NNNN]. Subunit A is represented as the tan ribbon structure with the 5Y-CAP domain highlighted in green while the Toprim domain is highlighted in yellow. The tyrosine active site is colored magenta within the 5Y-CAP domain. Blue residues mark cold-sensitive spo11 alleles. Red residues are heat-sensitive alleles. Orange alleles fluctuate between cold and heat sensitivity depending on the temperature. The white allele is insensitive to temperature. The Mg2+ metal ion in the Toprim region is shown as a small green sphere. Subunit B is colored in gray. B) spo11 alleles are listed alongside their affected residues, their temperature sensitivities, whether the residues are conserved and their location in the protein domain. Symbols show which residues correspond with which domain. “Varies” means that the residue can be cold and heat sensitive depending on the temperature range. No structural alignment means that the crystal structure was unavailable. Conservation refers to the original residue.Description of (EPS)Click here for additional data file.Figure S2ARG4 region hotspots equally for initiation (red lines). Prototroph (C) and CO association frequencies (D) were simulated using wild-type tract length parameters either using predicted changes in CO/NCO ratios (red lines) or constant ratio (blue lines).Contribution of CO and NCO ratios and tract length changes on simulations. Black lines indicate values obtained for simulations using the predicted  changes in CO/NCO ratio as well as tract length changes for simulated prototroph frequencies (A and C) and CO association (B and D). Prototroph frequencies (A) and CO association frequencies (B) were simulated using the three (EPS)Click here for additional data file.Figure S32 = 0.6), indicating the trend of more COs per total events as Spo11 activity declines. B–F, Distributions of GC tract lengths associated with NCOs (B) and COs (C–F). Log-normal curves were fitted for WT, HI and LO to determine the underlying distribution parameters (means and SDs). Mean tract lengths were then extrapolated for strains with 30, 10 or 3 COs, using either a linear regression (B and C) or various non-linear regressions including square-root (D), log (E) or inverse (F) functions of X (X being the number of COs). In all cases, SDs of GC tract length distributions were obtained using linear trends. CO tract length log-normal distributions for WT (solid black line), HI (red), LO (blue), and 30 COs (green), 10 COs (purple) and 3 COs (yellow) simulated mutants are plotted, along with their respective means (dotted lines). G. Representation of linear and non-linear regression curves  used to extrapolate the mean of the CO tract length distributions for putative mutants with 30, 10 and 3 COs . The x-axis represents the number of COs while the y-axis represents the mean of CO tract length distributions in base pairs.Extrapolated data for mutants with 30, 10 or 3 COs. A, COs as a percentage of total events were plotted against COs per tetrad based on sequence data from WT (black), HI (red) and LO (blue) tetrads. Four-chromatid double COs were counted as single events; in addition, both CO and NCO events in which there was a GC tract on two chromatids were counted as single events. A line (linear regression) was drawn through the points (R(EPS)Click here for additional data file.Figure S4Half vs. whole tracts. Black lines indicate values obtained for simulating Arg prototrophs (A) and CO association (B) using tracts initiating at the DSB hotspots. Red lines similarly show values for “half tracts”, in which the DSB hotspot would fall in the middle of the tract.(EPS)Click here for additional data file.Table S1Arg prototroph data.(XLSX)Click here for additional data file.Table S2Spore viability and SC formation.(XLSX)Click here for additional data file.Table S3Crossing-over in strains released from Ndt80 arrest and WT.(DOC)Click here for additional data file.Table S4Leu prototroph data.(XLSX)Click here for additional data file.Table S5Sequencing data for wild-type tetrads at various temperatures.(XLSX)Click here for additional data file.Table S6Strain list.(DOCX)Click here for additional data file.Text S1Methods.(PDF)Click here for additional data file.


Hypercapnic Chronic Obstructive Pulmonary Disease (COPD) exacerbation in patients with comorbidities and multidrug therapy is complicated by mixed acid-base, hydro-electrolyte and lactate disorders. Aim of this study was to determine the relationships of these disorders with the requirement for and duration of noninvasive ventilation (NIV) when treating hypercapnic respiratory failure.2 and PaCO2 and blood lactate were checked at the 1st, 2nd, 6th and 24th hours after starting NIV.Sixty-seven consecutive patients who were hospitalized for hypercapnic COPD exacerbation had their clinical condition, respiratory function, blood chemistry, arterial blood gases, blood lactate and volemic state assessed. Heart and respiratory rates, pH, PaONine patients were transferred to the intensive care unit. NIV was performed in 11/17 (64.7%) mixed respiratory acidosis–metabolic alkalosis, 10/36 (27.8%) respiratory acidosis and 3/5 (60%) mixed respiratory-metabolic acidosis patients (p = 0.026), with durations of 45.1±9.8, 36.2±8.9 and 53.3±4.1 hours, respectively (p = 0.016). The duration of ventilation was associated with higher blood lactate (p<0.001), lower pH (p = 0.016), lower serum sodium (p = 0.014) and lower chloride (p = 0.038). Hyponatremia without hypervolemic hypochloremia occurred in 11 respiratory acidosis patients. Hypovolemic hyponatremia with hypochloremia and hypokalemia occurred in 10 mixed respiratory acidosis–metabolic alkalosis patients, and euvolemic hypochloremia occurred in the other 7 patients with this mixed acid-base disorder.Mixed acid-base and lactate disorders during hypercapnic COPD exacerbations predict the need for and longer duration of NIV. The combination of mixed acid-base disorders and hydro-electrolyte disturbances should be further investigated. Hypercapnic respiratory failure is a complex condition associated with the malfunction of various organs and systems crucial for many physiological processes, leading to an acid-base imbalance.2) is not the only independent variable that may cause alterations in acid-base status. Total serum protein, albumin in particular, plays an important role, as does the strong ion difference (SID), that is the difference between the strong positive ions in the plasma (sodium (Na+), potassium (K+), calcium (Ca2+), and magnesium (Mg2+)) and the strong negative ions (chloride (Cl−) and lactate (Lac−)):+ for electroneutrality, with a change in [H+], and so a change in pH.Carbon dioxide  concentrations in the extracellular volume, whose total solutes consist almost entirely of Na+, Cl− and bicarbonate ions (HCO3−).Acid-base and electrolyte balance are part of the same picture because, for a given increase in COIn hypoxic and hypercapnic COPD patients, fluid homeostasis is disturbed, with avid retention of sodium and water In hypercapnic COPD exacerbations, the sudden decrease in ventilation causes an acute respiratory acidosis or deteriorates a pre-existing chronic respiratory acidosis. Due to the high prevalence of comorbidities This study had the following aims: to evaluate mixed acid-base, hydro-electrolyte and lactate disorders in patients with hypercapnic COPD exacerbation; to determine the relationship among these disorders, a poor response to pharmacological treatment and the requirement for noninvasive ventilation (NIV); and to analyze the link between these disorders and the duration of NIV in the treatment of hypercapnic respiratory failure.The institutional review board for human studies (Fondazione Eleonora Lorillard Spencer Cenci Ethics Committee) for human studies approved the protocol, and written consent was obtained from the subjects or their surrogates.2≥45 mmHg on arterial blood gas (ABG) analysis We investigated patients consecutively hospitalized in our respiratory ward  for COPD exacerbation and hypercapnic respiratory failure. Between January and April 2010, sixty-seven patients were consecutively hospitalized for COPD exacerbation and hypercapnic respiratory failure. COPD and COPD exacerbation were defined according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines Patients were excluded from this descriptive study if they had concomitant pneumonia, acute lung injury (ALI) or acute respiratory distress syndrome (ARDS), and contraindications to noninvasive ventilation (NIV) Baseline demographic characteristics and clinical parameters, routine blood chemistry and ABG were assessed at admission.The level of consciousness was assessed using the Glasgow Coma Scale +), urinary sodium (uNa+), plasma osmolality (Posm) and urine specific gravity (SG). TBW was expressed as a percentage of body weight . Body water deficit was calculated using the following equation:1) considered for the analysis were those measured subsequently at a stable clinical condition .Patients were classified into pure respiratory acidosis or mixed defect  categories 2) at least ≥90%, and conventional treatments, including nebulized bronchodilators, intravenous corticosteroids, antibiotics (if necessary) and other drugs, depending on the concomitant comorbidities. NIV was initiated when controlled oxygen therapy and convientional medical treatments failed to improve the clinical conditions, or rather when respiratory distress with accessory muscle use or abdominal paradox and tachypnea (respiratory rate >24/min) were associated with persistent arterial impairment  despite optimal pharmacological treatment and oxygen therapy 2 and PaCO2 and blood lactate were checked on the 1st, 2nd, 6th and 24th hours after starting NIV.Initially, all patients received controlled oxygen therapy with a Venturi mask, in order to maintain an arterial oxygen saturation , and the qualitative variables are summarized as frequency and percentage. The results are reported separately for each of the two groups (NIV use and no NIV use). The statistical analysis was conducted by parametric or non-parametric test, according to the distribution of variables as assessed by the Shapiro-Wilk test. Student's t-test for unpaired data was used to compare the quantitative variables between the two groups (NIV use and no NIV use), while the chi-squared test was used for qualitative variables. The unadjusted odds ratio (OR) for NIV use vs. no NIV use and its associated 95% confidence interval (95% CI) were calculated for each variable by a logistic regression analysis. One-way ANOVA for repeated measures was used with the clinical parameters, ABG results and lactate values to evaluate the effects of NIV use over 24 h. Contrast analysis, a priori specified, was used for comparisons versus previous time points.The differences in NIV duration among groups of patients identified according to the ABG analysis values  were evaluated using the Kruskal-Wallis H test. The Mann-Whitney U test with Bonferroni correction was applied to evaluate the differences of various parameters at each time point between respiratory acidosis patients and mixed respiratory acidosis–metabolic alkalosis patients. Linear regression analysis was applied to evaluate the relationships between NIV duration and various parameters.Statistical analysis was performed using SPSS Advanced Statistical 10.0 software .Between January and April 2010, 75 patients were consecutively hospitalized for COPD exacerbation and hypercapnic respiratory failure, but 67 were enrolled in the study population (5 patients were excluded for being on chronic NIV treatment at home and the other 3 for the presence of concomitant pneumonia).We considered 58 of the 67 patients initially enrolled, as 9 were excluded because they were transferred to the intensive care unit for pH<7.1, hypercapnic coma or hemodynamic instability .The enrolled COPD patients had multiple comorbidities, such as hypertension ; ischemic heart disease ; degenerative, hypertensive and valvular heart disease ; atrial fibrillation and other arrhythmias ; cor pulmonale ; peripheral artery disease ; diabetes mellitus ; chronic renal failure ; and obstructive sleep apnea syndrome . Therefore they were on multidrugs treatments including diuretics, ACE inhibitors, angiotensin receptor antagonists, digoxin, anti-arrhythmic drugs , oral hypoglycemic agents, insulin, allopurinol, aspirin, statins and inhaled bronchodilators.2O. Supplementary oxygen was administered during ventilation, which was continuous until clinical conditions were stable with pauses for administration of conventional medications, feeding and general care. None of the patients required the interruption of the ventilatory assistance for discomfort, or refused the treatment. The only complications recorded were 1 case of nasal cutaneous sores and 2 cases of gastric distension, neither of which required interrupting the ventilatory assistance.NIV was initiated in 24 patients and succeeded in correcting respiratory acidosis in all of them. The mean duration of NIV was 42.4±10.5 hours, and the mean IPAP employed was 16±4 cmHPatient demographics and clinical characteristics are shown in 2, PaO2/FiO2, alveolar–arterial PaO2 gradient, Na+, Cl−, pH and serum lactate; and higher PaCO2 and blood lactate , 17 patients with mixed respiratory acidosis–metabolic alkalosis  and other 5 with mixed respiratory-metabolic acidosis  .Patients with mixed respiratory acidosis–metabolic alkalosis were more likely to use NIV than those with the pure respiratory acidosis, and their NIV duration was longer . NIV was+ and Cl− concentrations, as shown by their regression coefficients .NIV duration was significantly associated with higher blood lactate, lower pH and lower serum Na2, PaCO2 and blood lactate improved in the first 6 hours of NIV (th and the 24th hour of ventilation in the mixed respiratory-metabolic acidosis patients (data not shown).In respiratory acidosis and mixed respiratory acidosis–metabolic alkalosis NIV patients, heart rate, respiratory rate, pH, PaOs of NIV , while sWe also evaluated hydro-electrolyte balance and identified 11 respiratory acidosis patients who had normochloremic hypervolemic hyponatremia due to chronic renal failure (n = 2), cirrhosis (n = 1), hypothyroidism (n = 1), or chronic congestive heart failure (n = 7).Of the patients with mixed respiratory acidosis–metabolic alkalosis, 10 had hypovolemic hyponatremia, hypochloremia and hypokalemia due to thiazide or loop diuretic use associated with diarrhea and vomiting during a gastroenteritis episode (n = 2), profuse sweating from febrile influenza syndrome (n = 4) or (probably) poor dietary fluid intake (n = 4). Euvolemic hypochloremia due to thiazide or loop diuretic use not associated with extrarenal hydro-electrolyte loss was detected in 7 patients with mixed respiratory acidosis–metabolic alkalosis.In mixed respiratory-metabolic acidosis patients, the metabolic acidosis was due to an exacerbation of chronic renal failure (n = 1), rhabdomyolysis (n = 1), ketoacidosis in decompensated insulin-dependent diabetes mellitus (n = 2) or metformin-related lactic acidosis (n = 1 obese diabetic patient).Hypercapnic respiratory failure during acute COPD exacerbation is an alarming event that requires careful management of the resulting respiratory acidosis. The final outcome depends on various factors, such as the patient's overall health status and concomitant comorbidities, the baseline lung function, and the disease severity as judged by the need for assisted ventilation and the degree of acidosis We observed that metabolic alkalosis with hyponatremia and/or hypochloremia aggravated the respiratory acidosis due to the COPD exacerbation. Mixed respiratory acidosis–metabolic alkalosis patients were more likely to use NIV and were subjected to longer periods of ventilation compared to those with pure respiratory acidosis. The requirement for and duration of NIV was associated with low serum sodium and chloride, common findings in diuretic-induced metabolic alkalosis. The clinical parameters and ABG analysis indicated more severe ventilatory impairment in the patients with mixed respiratory acidosis–metabolic alkalosis than in those with pure respiratory acidosis, with the exception of those with an elevated pH due to a simultaneous alkalinizing processes.In patients with hypercapnic respiratory failure due to COPD exacerbation, the presence of a sufficient metabolic compensation and adequate renal function significantly decreases mortality 2 and lower pH toward normal levels Metabolic alkalosis causes a direct depression of the respiratory drive, leads to diminished chemoreceptor stimulation and consequently reduces alveolar ventilation to increase PaCOMetabolic alkalosis is usually associated with hypochloremia, which has a relevant inhibitory effect on the ventilatory response to hypercapnia. A reduction of serum chloride is associated with a reduced chloride concentration in the cerebrospinal fluid In addition, metabolic alkalosis has been associated with increased airway resistance I) and mouth occlusion pressure (P0.1) to changes in PaCO2, while we investigated the possible deleterious effects of metabolic alkalosis on the ventilatory response to hypercapnia by assessing the requirement and duration of NIV in a real clinical scenario.In a study investigating the effects of metabolic acid-base changes on central ventilatory chemoregulation in normocapnic and hypercapnic COPD patients, the ventilatory responsiveness to carbon dioxide was not significantly altered by the induced metabolic state The effect of metabolic alkalosis on the clinical outcome of COPD patients was first reported in a study that showed an improvement in gas exchange and clinical symptoms after correcting the coexistent metabolic alkalosis 2 by correcting metabolic alkalosis 2 and low PaO2. COPD patients with a tendency toward hypercapnia require extra attention because hypercapnia is believed to be an ominous sign for morbidity and mortality 2 caused by furosemide may lead to fluid retention, which may counteract the diuretic effects of furosemide. This is of clinical relevance, especially considering that loop diuretics are prescribed to a substantial number of COPD patients. Thus, other types of diuretics should be considered when diuretic therapy is indicated in hypercapnic COPD patients. Spironolactone, which causes no acid/base shifts, or acetazolamide, which causes a metabolic acidosis, may be better options. Because loop diuretics are often necessary in COPD patients with cor pulmonale or cardiac comorbidities, acetazolamide could be added to counteract the metabolic alkalosis Discontinuing furosemide, which is prescribed for peripheral edema in patients with stable COPD, increases the minute ventilation and lowers the PaCOLactate clearance, as a surrogate for the magnitude and duration of global tissue hypoxia, is used for diagnostic, therapeutic and prognostic purposes. The normal reference values for lactate are traditionally considered 1±0.5 mmol/l in normal patients and <2 mmol/l in critically ill patients Increased lactate production indicates increased anaerobic metabolism associated with tissue hypoxia; lactate is one of the intermediate products that increase as a consequence of metabolism derangement during hypoxia Lactate clearance is a useful prognostic indicator. It reveals improvements in systemic tissue hypoxia and is associated with a decreased mortality rate. Patients with greater early lactate clearance after 6 hours of intensive care treatment have better outcomes than do subjects with lower lactate clearance In addition, early lactate clearance is significantly associated with decreased levels of inflammatory biomarkers, improvements in organ dysfunction and improved outcomes in severe sepsis and septic shock 2 saturation and PCO2 can offer a precise “local” picture of cellular oxygen disturbance, lactate does not. Nevertheless, systematically checking lactate clearance could be used to tailor the therapy in many cases of respiratory insufficiency In patients with respiratory failure, the early lactate clearance could be useful to assess the metabolic response to therapy and to identify individuals who are able to reverse the metabolic derangement. Lactate clearance deserves the same diagnostic relevance as other noninvasive markers of delivery/consumption/demand mismatches. While tissue pH, OThe greatest amounts of lactate are produced by the skin, erythrocytes, skeletal muscles, and leukocytes We considered blood lactate as a diagnostic marker of tissue hypoxia and respiratory muscle fatigue , an indirect indicator of hypercapnic COPD exacerbation severity and, as a consequence, an indirect indicator of its response to treatment.3− and the anion gap, but should rely on a more comprehensive evaluation + concentration. While there are tissues whose deranged metabolic pathways need lactate as an intermediate metabolite to survive, the production of lactate itself depends on pH In our study, lactate improved over time once NIV was started. Patients with higher blood lactate were more likely to require NIV and needed longer ventilation times. The effects of hyperlactatemia on pH were attenuated in patients with concomitant hypochloremic metabolic alkalosis. Therefore, acid-base analysis should not only be based on traditional parameters, such as pH, HCOIn this study we identified a few patients with mixed respiratory-metabolic acidosis who required long NIV periods. Metabolic acidosis stimulates hyperventilation, but these patients had impaired ventilation, probably as a result of muscle wasting due to the metabolic academia In this descriptive study, we did not analyze the subgroups derived from the combinations of mixed acid-base disorders and hydro-electrolyte disturbances because the number of patients was not sufficient to guarantee a significant statistical power for this purposeProbably the descriptive design of the study does not allow us to obtain definitive conclusions, but we strongly believe to have investigate a field not yet explored, eventually stimulating further prospective multicentric studies in order to completely clarify this topic, which recurs frequently in clinical practice.Our preliminary results suggest, in fact, that in the clinical respiratory care researchers should address the following questions: a) whether lactate clearance is useful during acute respiratory failure to identify patients at high risk of negative outcomes and, potentially, to increase the intensity of the therapeutic approach; b) whether lactate clearance is predictive of positive outcome and could confirm to physicians that the current therapeutic approach is appropriate; and c) how both the metabolic components of mixed acid-base disorders and the hydroelectrolyte balance alterations may worsen the hypercapnic respiratory failure caused by the COPD exacerbation and may affect its resolution through standard medical therapy, either alone or combined with NIV.


Nutrient enrichment of high-elevation freshwater ecosystems by atmospheric deposition is increasing worldwide, and bacteria are a key conduit for the metabolism of organic matter in these oligotrophic environments. We conducted two distinct in situ microcosm experiments in a high-elevation lake  to evaluate responses in bacterioplankton growth, carbon utilization, and community structure to short-term enrichment by nitrate and phosphate. The first experiment, conducted just following ice-off, employed dark dilution culture to directly assess the impact of nutrients on bacterioplankton growth and consumption of terrigenous dissolved organic matter during snowmelt. The second experiment, conducted in transparent microcosms during autumn overturn, examined how bacterioplankton in unmanipulated microbial communities responded to nutrients concomitant with increasing phytoplankton-derived organic matter. In both experiments, phosphate enrichment (but not nitrate) caused significant increases in bacterioplankton growth, changed particulate organic stoichiometry, and induced shifts in bacterial community composition, including consistent declines in the relative abundance of Actinobacteria. The dark dilution culture showed a significant increase in dissolved organic carbon removal in response to phosphate enrichment. In transparent microcosms nutrient enrichment had no effect on concentrations of chlorophyll, carbon, or the fluorescence characteristics of dissolved organic matter, suggesting that bacterioplankton responses were independent of phytoplankton responses. These results demonstrate that bacterioplankton communities in unproductive high-elevation habitats can rapidly alter their taxonomic composition and metabolism in response to short-term phosphate enrichment. Our results reinforce the key role that phosphorus plays in oligotrophic lake ecosystems, clarify the nature of bacterioplankton nutrient limitation, and emphasize that evaluation of eutrophication in these habitats should incorporate heterotrophic microbial communities and processes. Warming trends are disproportionately altering these habitats Evidence for eutrophication in these habitats is based largely on increases in phytoplankton abundance inferred from long-term trends in particulate organic matter e.g. . HoweverStudies simultaneously evaluating the direct impact of nutrient enrichment on bacterioplankton growth, DOM consumption, and community composition are rare, and are highly relevant to understanding how eutrophication may impact oligotrophic environments such as high-elevation lakes. Previous work investigating bacterioplankton has concentrated on the interaction of inorganic nutrients and carbon in controlling bacterial metabolism, stemming from the assumption that bacterioplankton are carbon limited in situ nitrate- and phosphate-enrichment microcosm experiments in a well-characterized Sierra Nevada lake known to be impacted by ongoing eutrophication This study sought to clarify the nature of bacterial nutrient limitation in high-elevation lakes of the Sierra Nevada: how nutrient loading directly alters the growth rates, DOM consumption rates, and taxonomic composition of bacterioplankton communities. To test the hypothesis that bacterioplankton in these systems exhibit nutrient limitation independent of indirect phytoplankton responses and in the context of seasonal shifts in DOM source pools, we conducted two distinct max), solute chemistry, and catchment composition This research was conducted in Emerald Lake, a cirque lake located on the western slope of the south-central Sierra Nevada . Research permits for this study were provided by Sequoia-Kings Canyon National Park. The lake, situated at 2800 m a.s.l. in a sparsely forested granitic catchment, is representative of the >4000 high-elevation lakes  scattered throughout the Sierra Nevada in size  which had been leached with 10% HCl for three days, rinsed, dried, then leached again for several hours with water from Emerald Lake just prior to deployment at 2 m depth in the center of the lake suspended on a subsurface-bouyed and anchored thermistor array line. Each experiment consisted of three replicated treatments: treatment (P) was enriched by ∼1.5 µmol L−1 K2HPO4, treatment (N) was enriched by ∼10 µmol L−1 KNO3, and an unamended Control treatment was enriched with a comparable volume (1‰) of distilled water. These amendment concentrations were selected to double regional maxima of dissolved N and P in accordance with long term trends in Sierra Lakes −1 in Sierra Nevada Lakes and ambient nitrate concentrations vary widely with snowmelt conditions with seasonal means typically between 3 and 9 µmol L−1Two separate −1 to 15.9 µmol L−1 and mean soluble reactive phosphate (SRP) levels from 0.04 µmol L−1 to 1.6 µmol L−1, altering mean starting DIN:total phosphorus (DIN:TP) molar ratios to 2.7, 161, and 59 for P, N, and Control treatments respectively.Each experiment used lakewater collected from a discrete 2 m depth interval in the center of the lake with biogeochemical variables and bacterioplankton community structure representative of the entire water column at each time −1 to 9.78 µmol L−1 and mean SRP levels from 0.04 µmol L−1 to 1.8 µmol L−1, altering mean starting DIN:TP molar ratios to 0.3, 86, and 5.8 for P, N, and Control treatments respectively. Nutrient amendments in both experiments successfully enriched inorganic nutrient concentrations in treated microcosms above background levels throughout the duration of the experiments (RM-MANOVA between-subjects treatment effect p<0.01). The DIN:TP ratios represent the extremes of the historical range of observed environmental ratios found in Emerald Lake  was conducted using nine microcosms (three replicates assigned to each of three treatments) constructed of transparent polyethylene filled with 7.5 L whole lakewater collected from the center of Emerald Lake at 2 m depth and promptly amended with nutrients as described above. Nutrient enrichment in the LIGHT experiment increased mean DIN levels from 0.45 µmol L−1 d−1) and presumably contributed little to fresh DOM production at that time. The DARK experiment was conducted for one week  when the lake was characterized by rapid flushing (residence time 12 days), the onset of post-iceoff stratification , low chlorophyll a (Chl a) concentrations (mean epilinion concentrations 0.25 µg L−1), and DOM derived largely from terrestrial sources (DOM fluorescence index (FI) of 1.27; −1 d−1). The LIGHT experiment was conducted for twelve days  when the lake was characterized by longer hydraulic residence time (209 d), post-stratification mixing , elevated Chl a concentrations (0.74 µg L−1), and an increasing contribution of autochthonous DOM sources , respectively. DOC and FDOM samples were collected in precombusted amber glass EPA vials with teflon septa, acidified and frozen . Samples for 3H-leucine incorporation consisted of 30 mL whole water collected in acid-washed triple-rinsed polycarbonate centrifuge tubes with polyethylene lids  just before departure from the field site and were enriched with 3H-leucine immediately upon return to the laboratory, maintaining in situ temperatures using insulated pack-coolers throughout travel. Sample collection and handling methods for DNA, prokaryotic abundance, and chlorophyll followed Nelson For each sample (collected every one to three days), microcosms were removed from the lake for two to three hours for processing. Samples collected and parameters measured included the following: particulate carbon, particulate nitrogen, and particulate reactive phosphorus ; total dissolved nitrogen and phosphorus ; dissolved organic carbon (DOC); dissolved inorganic nitrate + nitrite (DIN); dissolved soluble reactive phosphorus (SRP); prokaryotic abundance; DNA. In addition, LIGHT microcosms were sampled for fluorescent dissolved organic matter (FDOM), Chl 2O blank measured on a Shimadzu RF-1501 spectrofluorometer. Bacterial density was determined by epifluorescence microscopy of 2% formalin-preserved specimens stained with the nucleic-acid fluor DAPI  at a final concentration of 5 µg mL−13H-leucine incorporation was measured by incubating 1.7 mL whole water samples in a chilled flowing water bath maintained at in situ temperatures with 20 nmol L−1 L- leucine  for 90 to 120 minutes and processing according to the microcentrifuge method of Smith and Azam The DOM fluorescence index FI;  was usedin silico TRF length are classified with >95% probability by Bayesian classifier Terminal restriction fragment length polymorphism (TRFLP) of 16S ribosomal subunit DNA genes amplified by the polymerase chain reaction was used as a DNA fingerprinting method for comparison of bacterial community composition Repeated measures multivariate analysis of variance  was used to test the between-subjects null hypothesis of no difference between nutrient-enriched and control treatments across sampling times for a suite of response variables. Replicate microcosms were grouped according to treatment within each timepoint and separate analyses were conducted for each response variable comparing each nutrient with the control. Explicitly, a repeated-measures MANOVA was conducted comparing Control and Treatment replicate groups (separate RM-MANOVA for each N vs. Control and P vs. Control) for each response variable testing the individual effects of time (within-subject effect) and treatment (between-subject effect) and their interaction (time by treatment). The repeated-measures design accounts for within-microcosm variation through time and the MANOVA approach avoids Type I errors caused by violations of the sphericity assumption associated with univariate RM-ANOVA analysis frameworks TRFLP data from all samples were aligned and analyzed using a novel frequency-based alignment method to avoid the errors associated with integer-based fragment length “binning” −1; In the DARK experiment, P addition increased both the density and growth rates of bacterioplankton above that of both Control and N treatments . ChangesIn the LIGHT experiment, leucine incorporation rates in the P treatment increased two- to four-fold above rates in both Control and N treatments and this increase was both rapid and sustained . The LIGAlthough all bacterial and biogeochemical variables were measured identically in both experiments  only a subset of particulate organic variables showed significant differential responses . PhosphoOrdination of TRFLP data via nonmetric multidimensional scaling (NMS) revealed that bacterial community composition shifted through time in both experiments . Community structure differences within microcosms between the start and end of the experiment were especially high in the LIGHT experiment (up to 80% difference), indicating a strong temporal shift within the microcosms, but the treatments did not differ significantly in the magnitude of change through time in either experiment (ANOVA p>0.05 in both experiments). There was no significant difference in community composition between treatments at the start of either experiment , nor did treatments differ in the degree of community similarity among replicates at any time (ANOVA p>0.05 in both experiments), demonstrating that filtration and mixing manipulations were applied consistently among treatments and replicates in both experiments. The magnitude of variation between treatments at the start of the experiment was equivalent to the magnitude of variation among replicates , but temporal variation was roughly twice as large , indicating significant community shifts within all microcosms through time. The mean Sørensen distance between P and Control treatments at the end of the experiment was significantly greater than the mean Sørensen distance between N and Control Treatments (t-test p<0.05 in both experiments).Responses of specific bacterial taxa to nutrients differed in the two experiments, reflecting the differences in manipulated and unmanipulated communities as well as the difference in available organic and inorganic nutrient pools at the time of the experiments . At the In this manuscript, we have quantified in a single ecosystem how a “P pulse” affects bacterial growth (both cell doubling and leucine uptake), organic matter consumption, bacterial growth efficiency, bacterial community structure, and the nutrient stoichiometry of organic matter. We have also contrasted phosphate effects with those of nitrate, another potential agent of eutrophication in these systems. Specifically, our results demonstrate that phosphorus enhances bacterial uptake of extant allochthonous DOM in the dark , enhanceThe rapid P-enrichment response in leucine uptake exhibited by the microbial community in the LIGHT experiment  and the The two experimental approaches provide complementary assessments of microbial growth responses to nutrients. Although the DARK experiment allows simultaneous direct measurement of bacterial growth rates and DOC removal rates , it requPrevious studies experimentally examining temporal variability in the relationship between nutrient availability and prokaryotic production in high-elevation lakes have revealed similar trends to those observed in this study. Villar-Argaiz, et al. Phosphate enrichment increased the rate of DOC removal during the DARK dilution culture experiment . This reBecause significant DOC removal occurred in the DARK Control treatment, we can infer that the bacterioplankton were not carbon-limited and that P-enrichment only enhanced uptake of an already bioavailable DOM pool. Sadro et al. in silico digest lengths, none of which appear to be a major contributer to the patterns of community differentiation shown in Although bacterial growth was enhanced by P amendment in both experiments we cannot say if DOC uptake may have been transferred to higher trophic levels or been respired by bacterioplankton. However, the stoichiometric shifts in particulate nutrient concentrations observed in response to P-enrichment  togetherThe compositional shift in the bacterioplankton community in response to P-enrichment  was signin situ hybridization or quantitiative polymerase chain reaction would help to clarify these responses.In the present study, Actinobacteria declined in response to P enrichment throughout both experiments , Table 1Prochlorococcus and one Synechococcus; e-values<1E−170 with identities >96%); while the depth of our cloning analysis is insufficient to accurately assign a genus-level identification, our observations . Maximum likelihood dendrogram is built using RaxML from clones aligned to the SILVA curated 16S alignment  using the SINA aligner. Colors overlying clades are matched to specific TRF lengths and named according to concensus classification using Bayesian analysis  of the SILVA taxonomy. Clones are derived from randomized clone libraries reported in Nelson (2009) and leaves are labeled according to clone name (library_well), representative GenBank Accession (one clone from each 97% sequence identity OTU was accessed), and in silico TRF length. All clones are detailed in (PDF)Click here for additional data file.Table S1Means and standard deviations of environmental parameters at the start of the DARK and LIGHT experiments and t-test for significant differences between the two dates. Variables exhibiting different mean values between the two dates (p<0.05) are highlighted in bold. For each experiment six samples are averaged, three before the start of the experiment and three from end of the experiment. The three samples are collected from 0.1 m, 2 m, and 4 m depth in the epilimnion of Emerald lake.(PDF)Click here for additional data file.Table S2Clones used to assign monophyletic concensus taxonomies to specific TRFs. Each clone is associated with a representative GenBank Accession number in the same 97% sequence identity cluster according to Nelson (2009). Each clone has an associated in silico TRF length. Representative clones were run through manual TRFLP in duplicate to derive a measured amplicon TRF length. Taxonomic assignments are done by Bayesian analysis of clone alignment within the SILVA reference curated 16S alignment to assign a putative identification. Confidence values are listed in parentheses (blanks<95).(PDF)Click here for additional data file.


In contrast, non-CSCs preferentially responded by cell cycle arrest, but were not eliminated by metformin treatment. Mechanistically, metformin increased reactive oxygen species production in CSC and reduced their mitochondrial transmembrane potential. The subsequent induction of lethal energy crisis in CSCs was independent of AMPK/mTOR. Finally, in primary cancer tissue xenograft models metformin effectively reduced tumor burden and prevented disease progression; if combined with a stroma-targeting smoothened inhibitor for enhanced tissue penetration, while gemcitabine actually appeared dispensable.Pancreatic ductal adenocarcinomas contain a subset of exclusively tumorigenic cancer stem cells (CSCs), which are capable of repopulating the entire heterogeneous cancer cell populations and are highly resistant to standard chemotherapy. Here we demonstrate that metformin selectively ablated pancreatic CSCs as evidenced by diminished expression of pluripotency-associated genes and CSC-associated surface markers. Subsequently, the ability of metformin-treated CSCs to clonally expand  Pancreatic ductal adenocarcinoma (PDAC) remains one of the most devastating cancers, and is the fourth leading cause of cancer-related deaths in industrial countries with a 5-year survival rate of less than 5% The primary systemic effect of metformin (Met) represents a decrease in blood glucose levels via reduced hepatic gluconeogenesis and increased glucose uptake in peripheral tissues Unlike the majority of differentiated cells within the tumor, CSCs have been shown to be highly resistant to chemotherapy in vitro as anchorage-independent three-dimensional spheres, which are enriched for cells with stem cell-like properties in vitro experiments all cells were freshly isolated from early passage xenografts and cultured in low passages as adherent cells or anchorage-independent spheres. Spheres are enriched in CD133+ cells  and several other markers that have been associated with a CSC phenotype as compared to adherent cells We have previously shown that primary pancreatic CSCs can be enriched First, we established the expression of the organic cation transporter 1, 2, and 3 (OCT1-3) in our primary PDAC cells Fig. 1A, & S1B) via inhibition of the expansion of the progenies of CSCs, which represent the bulk of the cells of the formed spheres. Even more importantly, we found that metformin significantly decreased the number of actually formed spheres with the same efficiency at 3 and 10 mM  and invasive capacity . Next, we analyzed the cell-cycle profile of adherent cells versus CSCs by flow cytometry. Interestingly, the data showed that the functional effect of metformin on cell cycle progression was much more marginal for sphere-derived cells suggesting a distinct mechanism responsible for their subsequent loss during extended treatment  with no apparent difference to non-CSC (data not shown). Moreover, we observed a similar net decrease in p70S6K, suggesting an efficient blockade of the mTOR pathway . As the mTOR pathway is a central regulator of autophagy, we analyzed whether metformin might induce characteristic hallmarks of autophagy in CSCs versus non-CSCs, but our results do not support the notion that the selective elimination of CSCs by metformin can be rationalized by alterations in autophagy . To provide further evidence that AMPK/mTOR pathway is not mediating the deleterious effects of metformin on CSCs, we investigated if the effects of metformin are mimicked by the direct AMPK activator A769662 and/or the mTOR inhibitor rapamycin (Rapa). Strikingly, neither sphere formation .Next, we hypothesized that the particular sensitivity of CSCs to metformin might be attributable to anti-oxidant properties to metformin in vivo using a brief 7-day metformin treatment of PDAC-185. During the subsequent follow-up of 40 days we observed a significant reduction in tumor growth and a complete remission in 3 out 8 tumors for metformin treated-mice as opposed to no remission in the control group . Consistent data were obtained for other PDACs with metformin monotherapy being highly effective in inducing disease regression . Secondly, tumors slowly, but regularly relapsed after withdrawal of metformin on day 100 . Thirdly, while the addition of gemcitabine in vitro showed an additive effect on the CSC population  tumor microenvironment. It is an emerging paradigm that normal stem cells are characterized by predominant aerobic glycolysis and suppressed mitochondrial oxidation with subsequently lower mitochondrial ATP production and ROS release in vitro as well as reduced tumor mass and prolonged remission more effectively in vivo than either drug alone in vitro, our in vivo treatment studies suggest that gemcitabine is actually dispensable as long as metformin is continued throughout the study. While these data certainly warrant further validation it appears reasonable to speculate that metformin monotherapy could represent a novel treatment option for patients that are too fragile to tolerate the side effects of the chemotherapeutic agent gemcitabine The ability of metformin to selectively eliminate CSCs is in stark contrast to the effects of gemcitabine, a chemotherapeutic drug that kills bulk cancer cells, but not cancer stem cells Unfortunately, however, all tested tumors eventually progressed under metformin therapy. It remains to be determined if CSCs exposed to long-term metformin treatment switch their metabolic phenotype rendering them resistant to metformin's effects on mitochondria (acquired resistance) or whether a preexisting subpopulation of CSCs is actually resistant to metformin and eventually becomes the dominating clone (inherited resistance). This issue should be addressed in future studies by comparing CSCs isolated from tumors that regressed under metformin treatment and CSCs isolated from tumors that eventually progressed under the same conditions. Extensive characterization of resistant clones should provide crucial insights as to whether this is actually preventable or second line treatment options could be offered.Importantly, however, the addition of a stroma targeting smoothened inhibitor appears mandatory to achieve stronger and longer lasting response rates. The most likely explanation could be two fold. One contributing factor to the failure of systemic therapies may be the abundant tumor stromal content that is the characteristic of PDAC. The stroma represents the majority of the tumor mass, and consists of a dynamic assortment of extracellular matrix components and non-neoplastic cells including fibroblastic, vascular, and immune cells. Recent work has revealed that the stroma supports CSCs, in vitro studies, albeit already significantly lower than those utilized in previous studies, are still non-achievable in vivo and therefore irrelevant from a mechanistic point of view. However, it is important to note that metformin accumulates in tissues and particularly in mitochondria at concentrations several-fold higher than those measured in blood in vitro studies are indeed highly relevant for the in vivo setting.It may be argued that the metformin concentrations used in our Metformin bears an exceptional safety profile as only hepatocytes, but not other non-transformed (stem) cells express OCT for efficient cellular uptake of metformin. Several clinical trials  are currently testing metformin in locally advanced and metastatic PDAC. This will hopefully provide a definitive assessment of the clinical effects of metformin in PDAC. It would be of particularly interest whether patients will also ultimately progress during metformin treatment and whether this could be assessed and/or predicted by the analysis of circulating cancer (stem) cells. Their prospective isolation during relapse may provide important mechanistic insights into the cause of relapse.After written informed consent had been obtained from the patients, excess tissues from resected pancreatic carcinomas was xenografted at Johns Hopkins Medical Institutions  and Hospital de Madrid - Centro Integral Oncológico Clara Campal , respectively, under the indicated Institutional Review Board-approved protocols For in vitro studies, tissue fragments were minced, enzymatically digested with collagenase  for 90 min at 37°C 3 cells/ml were seeded in ultra-low attachment plates  as described previously.PDAC spheres were generated and expanded in DMEM-F12  supplemented with B-27  and bFGF . 103 pieces of primary, in vivo expanded pancreatic cancer tissue pieces were either orthotopically or subcutaneously implanted into the pancreas of 6–8 weeks old female nude mice (Harlan Europe) as described previously 3). Size and weight of the pancreatic tumors were monitored. Gemcitabine was administered biweekly . Metformin was administered daily via i.p. injections  or the drinking water (150 mg/kg BW). SIBI-C1 was administered twice daily via i.p. injection .All animal experiments were conducted in accordance with institutional guidelines and were approved by the Institutional Animal Care and Use Committee of the CNIO (Protocol PA34/2012 – “Xenotransplant model for human pancreatic cancer”). Animals were housed and maintained in laminar flow cabinets under specific pathogen-free conditions. Briefly, 8 mmMaterials and Methods S1.More information can be found as Figure S1(related to &) Metformin targets pancreatic cancer stem cells. (A) Adherent and sphere-derived cells isolated from different PDAC tissues were treated for 7 days with metformin or control and analyzed for CD133 expression by flow cytometry (gates were set according to the respective isotype control). (B) Sphere formation capacity after treatment for 7 days with metformin or control. Representative images for the respective PDACs are shown (n≥3).(TIF)Click here for additional data file.Figure S2(related to) Metformin specifically eliminates cancer stem cells. (A) Quantification of scrape-induced migration after 24 h of treatment with metformin or control (n = 3). (B) Western blot analysis for cyclinD1 expression in adherent and spheres treated with 3 mM of metformin for 7 days. Quantification is shown relative to the housekeeping gene GAPDH and normalized to control (n≥3).(TIF)Click here for additional data file.Figure S3(related to) Role of autophagy. (A) qPCR analysis of ATG12 in adherent and spheres treated with 3 mM of metformin for 7 days. Data are normalized to the housekeeping gene. ATG12 as a marker for autophagy was not consistently altered by metformin in the different tumors and did not show distinct alterations between CSCs versus non-CSCs. (B) Western blot analysis for LC3 expression in adherent and spheres treated with 3 mM of metformin for 7 days. Also on the protein level, only slightly increased LC3b expression was detected after the treatment with metformin both in spheres and adherent cells as well as in tumors xenograft treated with metformin in vivo (n≥3).(TIF)Click here for additional data file.Figure S4(related to) Role of AMPK/mTOR. (A) Mitochondrial ROS production after 8 hours of treatment with metformin (Met 3 mM), AMPK activator A769662 (10 µM), or rapamycin (Rapa 10 ng/ml). (B) Mitochondrial transmembrane potential after 8 hours of indicated treatment (n≥3).(TIF)Click here for additional data file.Figure S5(related to ) In vivo targeting of pancreatic cancer stem cells. (A) PDAC-185 cells were implanted into immunocompromised mice and treatment was allocated on d7 after initial tumor take was verified. Mice were treated with metformin alone until d14. During the subsequent follow-up we observed a significant reduction in tumor growth and a complete remission in 3 out 8 tumors for metformin treated-mice as opposed to no remission in the control group (n = 6). (B) Subsequent immune-histochemistry analysis on day 40 and therefore 26 days after termination of metformin treatment, revealed an increase in necrotic areas of tumors treated with metformin and a consistent decrease in expression of CyclinD1 and pp7056K. (C) qPCR analysis for stem cell genes on day 40 and therefore 26 days after termination of metformin treatment.(TIF)Click here for additional data file.Table S1List of utilized primers.(TIF)Click here for additional data file.Materials and Methods S1Western Blot Analysis, Measurement of intracellular ATP levels, RNA preparation and RT-PCR, Flow cytometry, Invasion and migration assay, Clonogenic assay, Apoptosis assay, Immunohistochemistry, Cell-cycle analysis.(PDF)Click here for additional data file.


Necdin, a MAGE family protein expressed primarily in the nervous system, has been shown to interact with both nuclear and cytoplasmic proteins, but the mechanism of its nucleocytoplasmic transport are unknown.We carried out a large-scale interaction screen using necdin as a bait in the yeast RRS system, and found a wide range of potential interactors with different subcellular localizations, including over 60 new candidates for direct binding to necdin. Integration of these interactions into a comprehensive network revealed a number of coherent interaction modules, including a cytoplasmic module connecting to necdin through huntingtin-associated protein 1 (Hap1), dynactin and hip-1 protein interactor (Hippi); a nuclear P53 and Creb-binding-protein (Crebbp) module, connecting through Crebbp and WW domain-containing transcription regulator protein 1 (Wwtr1); and a nucleocytoplasmic transport module, connecting through transportins 1 and 2. We validated the necdin-transportin1 interaction and characterized a sequence motif in necdin that modulates karyopherin interaction. Surprisingly, a D234P necdin mutant showed enhanced binding to both transportin1 and importin β1. Finally, exclusion of necdin from the nucleus triggered extensive cell death.These data suggest that necdin has multiple roles within protein complexes in different subcellular compartments, and indicate that it can utilize multiple karyopherin-dependent pathways to modulate its localization. Necdin is a MAGE family protein mostly expressed in the nervous system, muscle and skin, which acts as a cell cycle regulator and plays a role in the differentiation or survival of both central and peripheral neurons In order to obtain a more comprehensive overview of the necdin interactome, we carried out a large-scale protein interaction screen with necdin as bait, identifying over 60 new candidate necdin binders. Integration of these interactions into a comprehensive necdin-centered network showed that it naturally decomposes into modules with distinct functions and subcellular localizations. The analysis revealed both nuclear and cytoplasmic modules and a nucleocytoplasmic transport module containing transportin1 and 2, members of the importin β family of nucleocytoplasmic transport factors. Exclusion of necdin from the nucleus affects cellular viability, and characterization of the necdin-transportin interaction indicate that necdin can utilize multiple karyopherin-dependent pathways to modulate its subcellular localization.Necdin, like other MAGE family proteins, does not have any known intrinsic catalytic activity and may signal by recruiting other molecules. In order to obtain a comprehensive view of necdin interaction partners, we used the RRS method We combined our screen data with a comprehensive network of published mammalian protein-protein interactions An overview of the necdin network reveals a modular structure with binding partners of diverse functional roles and cellular localizations such as the transcription factor p53, the nuclear transcription activator CREBBP, the membrane bound receptor p75 and the cytoplasmic adaptor MAGE D1. We applied a network-partitioning algorithm that divides the network into groups or modules, in a way that optimizes the modularity parameter Q Transportin 2 was found to interact with necdin in our RRS screen. Transportin 1 shares ∼84% sequence homology with transportin 2 in most species Although necdin has no known NLS or transportin-interaction motifs, we identified a sequence stretch in necdin amino acids 225–248 with some similarity to the proposed consensus for a transportin-interacting M9 motif To further study the effect of these residues on the interaction of necdin with other members of the karyopherin family, we transfected the mutants to HEK293 cells and carried out co-immunoprecipitations with transportin1 and with importin β1. Surprisingly, an interaction was also observed with importin β1, indicating that necdin can utilize multiple import pathways to the nucleus . The D23We further attempted to control subcellular localization of necdin by fusing the ORF with either NLS or NES sequences . Figure We carried out a large-scale analysis of necdin interactions based on an RRS protein-protein interaction screen in yeast. The network of necdin interactors thus identified displays a high degree of modularity and decomposes into nine main connectivity modules, with defined functional roles and cellular localizations. The RRS method does not require that the fusion proteins be targeted to the nucleus, potentially revealing a wider range of interactions than conventional two-hybrid methods The discovered modules confirm necdin's diverse roles as both a cytoplasmatic adaptor  and a nuclear factor (the p53-Crebbp module). Connections between the modules can shed futher light on possible roles of necdin, for example the connection between sirtuin1 (Sirt1) and p53. Necdin has been shown to regulate the acetylation status of p53 via Sirt1 to suppress p53-dependent apoptosis in postmitotic neurons Different studies have revealed changes in the subcellular localization of necdin upon signaling events or interactions with both nuclear and cytoplasmic proteins cdc25-2 yeast cells for screening of a mouse embryonic head cDNA library in pMyr as previously described Protein-protein interaction screens were conducted using the yeast Ras Recruitment System (RRS) Mouse protein-protein interactions for necdin were extracted from the IntAct database All cloned genes were from mouse origin, unless otherwise noted. We generated fusion constructs of the necdin ORF followed by either a triplicate SV40 NLS (sequence encoding DPKKKRKV repeated three times) in pHcRed1-nuc (Clontech), or a Keap1 NES (sequence encoding YLVQIFQELTL) I.p.'s, Western blots and immunofluorescence imaging were performed as previously described We used an Olympus laser-scanning confocal microscope  to image DAPI for nuclear staining and anti-HA for necdin staining. Quantification of necdin nuclear localization was carried out after manual segmentation, marking the cellular outline and the nuclear outline of all cells without an abnormal shape within each field. Abnormal shapes included cells with no nuclear staining and cells without an apparent cytoplasm, as well as cells that were not in focus in the chosen z-section. A Matlab script was used to quantify the total intensity within the cellular outline and the nuclear outline and then to calculate the ratio of total intensity within the nucleus to the total intensity within the entire cell, representing the fraction of the protein in the nucleus. Background intensity was subtracted from all values.For XTT assay , cells were supplemented with 2× medium and 1× tetrazolium salt reaction mixture (XTT reagent) with 1∶50 PMS (activation reagent). Cells were incubated at 37°C for 1–2 hours, followed by absorbance measurement at 450 nm, with subtraction of background measurements carried out at 630 nm. Live/dead assay (Molecular Probes) was performed according to the manufacturer's protocol.All parametric data are presented as mean ± standard errors (SE). Differences between mean values from each experimental group were examined with Students t test and were considered significant if p<0.05.Figure S1Mouse protein interaction network. The network was parsed from the IntAct database, complemented with the interactions detected in the present screen, and contains 2687 proteins (nodes) with 3817 interactions (edges). Necdin (NDN) is displayed in red. Blue edges denote published interactions, red edges are interactions detected in the present RRS screen.(TIF)Click here for additional data file.Figure S2MAGE H1 and MAGE H1-NES localization in PC12 cells. PC12 cells were transfected with MAGE H1 or MAGE H1-NES, and fixed after 48 hours. Cells were immunostained with anti HA (red) and DAPI (blue), and viewed under a confocal microscope.(TIF)Click here for additional data file.Table S1Results of Necdin RRS Screen.(XLS)Click here for additional data file.Table S2The necdin network.(XLS)Click here for additional data file.Table S3Module-enriched GO annotations.(DOC)Click here for additional data file.