Outlining microbial community dynamics during temperature drop and subsequent recovery period in anaerobic co-digestion systems

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<ul><li><p>Oa</p><p>LD</p><p>a</p><p>ARR2AA</p><p>KBKLRS</p><p>1</p><p>eob2bepictfttio</p><p>CT</p><p>h0</p><p>Journal of Biotechnology 192 (2014) 179186</p><p>Contents lists available at ScienceDirect</p><p>Journal of Biotechnology</p><p>j ourna l ho me page: www.elsev ier .com/ locate / jb io tec</p><p>utlining microbial community dynamics during temperature dropnd subsequent recovery period in anaerobic co-digestion systems</p><p>eticia Regueiro , Marta Carballa, Juan M. Lemaepartment of Chemical Engineering, Institute of Technology, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain</p><p> r t i c l e i n f o</p><p>rticle history:eceived 19 August 2014eceived in revised form6 September 2014ccepted 7 October 2014vailable online 16 October 2014</p><p>eywords:acteroidetes</p><p>a b s t r a c t</p><p>To improve the stability of anaerobic reactors, more knowledge is required about how the different com-munities react against operating perturbations and which specific ones respond better. The objectiveof this work was to monitor the changes in microbial community structure of an anaerobic digesterduring a temperature drop by applying different complementary molecular techniques. Temperaturedecrease led to an increase of Bacteroidales order, Porphyromonadaceae family and Bacteroides genus anda decrease in Syntrophomonas and Clostridium genera. Once the temperature was restored, the reactorrecovered the steady state performance without requiring any modification in operational conditions orin the microbiome. During the recovery period, Sedimentibacter genus and Porphyromonadaceae familyineticsow temperature performanceecovery periodyntrophomonadaceae</p><p>played an important role in the degradation of the accumulated volatile fatty acids. The hydrogenotrophicmethanogens appeared to be the keystone archaeal population at low temperatures as well as in therecovery period. This study stands out that the understanding of microbial community dynamics dur-ing temperature drop could be utilized to develop strategies for the mitigation of temperature changeconsequences and speed up the recovery of stable reactor performance.</p><p> 2014 Elsevier B.V. All rights reserved.. Introduction</p><p>Anaerobic digesters are often exposed to operational and/ornvironmental perturbations, such as temperature drops, organicverloadings, or the entry of toxic compounds, leading to insta-ility due to a stressed microbial community (Kleybcker et al.,012). Reactor microbiome responds differently to distinct distur-ances, resulting in an imbalance in the trophic network (Leitot al., 2006). This usually causes an accumulation of intermediateroducts, such as volatile fatty acids (VFAs), which may in turnnhibit microbial numbers, eventually reducing the process effi-iency. Allison and Martiny (2008) have indicated the necessityo understand the relationship between the microbiome and theirunction in the anaerobic process, especially in deteriorated sys-ems in order to identify those populations that better respond</p><p>o each individual operational stressor with the ultimate goal ofmproving the stability of anaerobic reactors and the control basedn microbial management.</p><p> Corresponding author at: Instituto de Investigacins Tecnolxicas (IIT)/Constantino Candeira s/n, 15782 Santiago de Compostela, Spain.el.: +34 881 816016; fax: +34 881 816702.</p><p>E-mail address: leticia.regueiro.abelleira@gmail.com (L. Regueiro).</p><p>ttp://dx.doi.org/10.1016/j.jbiotec.2014.10.007168-1656/ 2014 Elsevier B.V. All rights reserved.One common perturbation occurring in anaerobic reactors istemperature variations (Poh and Chong, 2009). Many studies haveinvestigated microbiomes in anaerobic reactors working at dif-ferent temperatures and they point out that community profilesvaried in each temperature range. Lee et al. (2012) detected alarge presence of Firmicutes in thermophilic range compared tomesophilic one, and the opposite trend for Bacteroidetes phylum.Leven et al. (2007) showed that Chloroflexi and Bacteroidetes rep-resented the major phyla at mesophilic temperatures, whilst thephylum Thermotogae was the dominant group in the thermophilicrange. In relation to the archaeal community, Methanomicrobialesdominated at 15 C, and Methanosaeta and Methanomicrobialeswere the most abundant at 37 C (Bialek et al., 2012). Summariz-ing, these studies confirm the temperature as a parameter affectingthe structure of the microbial communities, even more than theincrease in the organic loading rate (OLR) (Guo et al., 2014), butthey lack transient membership of the microbial community dur-ing the days of the temperature perturbation. Moreover, to the bestof our knowledge, there have been no studies published, whichmonitored the microbial community dynamics during the recov-</p><p>ery period after restoration of temperature. All this understandingcould be utilized to develop strategies for the mitigation of tem-perature change consequences and speed up the recovery of stablereactor performance based on microbial knowledge.</p><p>dx.doi.org/10.1016/j.jbiotec.2014.10.007http://www.sciencedirect.com/science/journal/01681656http://www.elsevier.com/locate/jbiotechttp://crossmark.crossref.org/dialog/?doi=10.1016/j.jbiotec.2014.10.007&amp;domain=pdfmailto:leticia.regueiro.abelleira@gmail.comdx.doi.org/10.1016/j.jbiotec.2014.10.007</p></li><li><p>180 L. Regueiro et al. / Journal of Biotech</p><p>Table 1Physico-chemical characteristics of pig manure (PM), molasses residues (MR) andfish waste (FW).</p><p>PMa MR FW</p><p>TS (g kg1) 50 15 835 304VS (g kg1) 40 10 707 282TKN-N (g N kg1) 3.1 1.0 57 19NH4+-N (g N kg1) 2.8 0.7 15 0.7CODtotal (g O2 kg1) 62 20 723 567TA (g CaCO3 kg1) 10.5 3.0 N.D. N.D.PA (g CaCO3 kg1) 4.5 2.0 N.D. N.D.Lipids (g kg1) N.D. N.D. 35</p><p>TS: total solids; VS: volatile solids; TKN-N: total Kjeldahl nitrogen; NH4+-N: ammo-nium; CODtotal: total chemical oxygen demand; TA: total alkalinity; PA: partiala</p><p>t</p><p>id(itmc(c</p><p>2</p><p>2</p><p>hw(mcst(dd</p><p>swis</p><p>2</p><p>2</p><p>2aTfddatGBmst</p><p>lkalinity; N.D: not detected.a Standard deviations are only shown for pig manure since different batches of</p><p>his substrate were necessary during the whole experiment (over 400 days).</p><p>Therefore, the objective of this work was to monitor the changesn microbial community structure of an anaerobic reactor not onlyuring a temperature drop from mesophilic (37 C) to psychrophilic17 C) range but also during the recovery period after restor-ng temperature to 37 C. The experimental design consisted ofwo types of perturbation (gradual and abrupt) and three comple-entary molecular techniques were applied to follow microbialommunity dynamics: Denaturing Gradient Electrophoresis GelDGGE), Fluorescence In Situ Hybridization (FISH) and a 16s rRNAharacterization with Illumina MiSeq platform sequencing.</p><p>. Materials and methods</p><p>.1. Substrates and inoculum</p><p>Pig manure (PM) was obtained from a fattening hog farm (3000eads) located in Santiago de Compostela (Spain). Fish waste (FW)as collected in a canning industry located on the Galician coast</p><p>Spain) and consisted of processing remains of albacore. Beetolasses residues (MR) were obtained from a sugar processingompany in A Coruna (Spain) and consisted of by-products of theugar-extraction process. Fish waste was grounded prior to use andhe substrates were stored at 4 C. All residues were characterizedTable 1) in terms of total and volatile solids content, total Kjel-ahl nitrogen and ammonium concentration, total chemical oxygenemand (COD), total and partial alkalinity, and lipid content.A mixture (50:50, v/v) of two anaerobic sludges, one from a</p><p>ewage sludge anaerobic digester and the second from a breweryastewater anaerobic reactor, was used as inoculum. The initial</p><p>n-reactor inoculum concentration was 15 g of volatile suspendedolids (VSS) per liter.</p><p>.2. Anaerobic digester operation</p><p>.2.1. Experimental setupOne continuously stirred tank reactor (160 rpm, Heidolph RZR</p><p>041), with a working volume of approximately 10 L, was oper-ted in two consecutive experimental runs (Experiments 1 and 2).he reactor was fed semi-continuously (once a day draw-off andeeding) with a mixture of PM, FW, and MR (602020, COD basis)uring both experiments. This mixture was prepared every week,iluted with tap water according to the applied OLR, and storedt 4 C. Temperature, pH, stirring speed, biogas production (Rit-er milligascounters, Dr. Ing. Ritter Apparatebau GmbH, Bochum,ermany) and biogas composition (AwiFLEX model from AWITE</p><p>ioenergie GmbH) were monitored on-line. Samples of reactorixed liquor were taken twice a week for VFAs, total COD, totaluspended solids (TSS), VSS, alkalinity and ammonium determina-ions. Biomass samples were taken weekly for molecular analysis,nology 192 (2014) 179186</p><p>except during the perturbation period, when a more frequentsampling was conducted (every 23 days).</p><p>2.2.2. Operational strategyExperiment 1 was divided in three periods: start-up (030 days),</p><p>gradual increase of OLR from 0.5 to 2 g COD L1 d1 and steady stateperformance at the latter OLR (31150 days), and the perturbationperiod (151195). The same periods were applied in Experiment 2,but the perturbation period lasted from day 151 to 161 and a fourthperiod, which we refer to as the recovery period (162212 days),was also included. In addition, the perturbation differed betweenboth experimental runs. In Experiment 1, a gradual temperaturedecrease was conducted by lowering the temperature from 37 to17 C at a rate of 2 C per day and keeping the latter temperatureconstant during the last 35 operating days (around 2 hydraulicretention times). The temperature was modified by adjusting thetemperature set point of the surrounding water bath. In Experi-ment 2, an abrupt perturbation (the temperature dropped from37 to 17 C (room temperature) in 24 h) was performed by turn-ing off the water bath. After working at 17 C for 10 days, thewater bath was again connected at day 161 (the temperature ofthe reactor rose to 37 C in one day) and maintained until theend of the Experiment 2. Moreover, the effect of using a differ-ent PM batch was also evaluated in Experiment 2, since typicallythe manure has different characteristics depending on the seasonalperiod.</p><p>2.3. Analytical methods</p><p>VFA (acetic, propionic, i-butyric, n-butiric, i-valeric and n-valeric) were analyzed by gas chromatography (HP, 5890A)equipped with a Flame Ionization Detector (HP, 7673A). COD, solids,TKN, ammonium, alkalinity and lipids were determined accordingto standard methods (APHA, 1998).</p><p>2.4. Molecular techniques</p><p>A selection of biomass samples were analyzed with DGGE plussequencing, FISH and also 16s rRNA characterization with the Illu-mina MiSeq platform with the main focus of determining themicrobial community dynamics during the perturbation and recov-ery periods. In this way, 21 samples from Experiment 1 (days 0, 15,48, 66, 85, 95, 104, 124, 135, 145, 150, 152, 154, 157, 159, 161, 164,171, 178, 185 and 194) and 14 samples from Experiment 2 (days0, 49, 98, 150, 152, 155, 157, 161, 164, 168, 173, 181, 197 and 211)were selected.</p><p>2.4.1. Denaturing gradient gel electrophoresis and sequencingDNA extraction, PCR, DGGE and sequencing were performed</p><p>according to Regueiro et al. (2012), based on the primers U968-fand L1401-r for Bacteria and the primers A109 (T)-f and 515-r forArchaea. Cluster analysis was conducted using Bionumerics soft-ware v.6.1 (Applied Maths, Sint-Martens-Latem, Belgium).</p><p>2.4.2. Fluorescent in situ hybridizationProbe sequences and formamide concentrations were applied</p><p>according to probeBase following the protocol explained byRegueiro et al. (2012). The probes used were: Eub338mix (Bacteria),CFX1223 (Chloroflexi), CFB562 (Bacteroidetes), LGC354 (Firmicutes),Arc915 (Archaea), Ms821 (Methanosarcina), Mx825 (Methanosaeta)</p><p>and MB1174 (Methanobacteriales). The abundance of each popula-tion was qualitatively evaluated by DAIME program (Daims et al.,2006). At least six photos were taken per 20 L of fixed sample.</p></li><li><p>L. Regueiro et al. / Journal of Biotechnology 192 (2014) 179186 181</p><p>Fig. 1. Volumetric biogas production and organic loading rate applied during Experiment 1 (A) and Experiment 2 (B) and volatile fatty acids concentrations in Experiment 1( turbe</p><p>2</p><p>5geffafiEcQa1iDCwa</p><p>upqt2twtu2apm</p><p>C) and Experiment 2 (D) during the last operational days, when the reactor was dis</p><p>.4.3. 16s rRNA characterization using Illumina MiSeq platformFor Illumina MiSeq, the extracted DNA was PCR amplified using</p><p>15-forward primers and 806-reverse Golay barcoded primers tar-eting the V4 region of the 16S rRNA gene according to Gilbertt al. (2010). The PCR cycle conditions consisted of 94 C for 3 minor initial denaturation; 25 cycles for denaturation at 94 C for 45 sollowed by annealing at 50 C for 60 s, elongation at 72 C for 90 snd final elongation for 10 min at 72 C. PCR products were con-rmed by gel electrophoresis and then cleaned using the MagBind-Z pure cleaning kit (Omega Bio-tek Inc., Norcross, GA, USA). DNAoncentration of the amplicons was quantified using Invitrogenuant-It Pico Green DNA quantification kit (Life Technologies, USA)nd samples were subsequently pooled at equimolar ratios (around00 ng of each sample). Libraries were sent in for pair-end sequenc-ng (2 250 bp) on the Illumina MiSeq platform (Illumina, Saniego, CA, USA) at the Cornell University Biotechnology Resourceenter (Ithaca, NY, USA). Only bacterial population was followedith Illumina, since the primers were not appropriate to study therchaeal community.Computational analysis of the sequencing reads was performed</p><p>sing the Quantitative Insights into Microbial Ecology (QIIME v1.7)latform (Caporaso et al., 2010). After joining the paired-end reads,uality filtering (using the default values in QIIME with the excep-ion that the minimum acceptable Phred quality score was set to5) and demultiplexing was performed. Closed-reference opera-ional taxonomic unit (OTU) picking with the default uclust methodas used to group sequences into OTUs at 97% identity. Represen-</p><p>ative sequences selected for each OTU were assigned taxonomysing the Greengenes reference database (Werner et al., 2011), May</p><p>013 version. OTU assignment resulted in 3362 OTUs total witht least one read per OTU. Principal coordinate analysis (PCoA)lot was generated based on weighted Unifrac pairwise distanceatrices.d.</p><p>3. Results and discussion</p><p>3.1. Anaerobic reactor performance</p><p>The first two periods were practically identical inboth experimental runs. During the start-up with anOLR of 0.50.7 g COD L1 d1, the biogas production was0.220.35 L L1 d1 (data not shown) corresponding to amethanization efficiency of 50%, while it increased up to0.850.95 L L1 d1 when the OLR increased to 2 g COD L1 d1(Fig. 1), with a methanization efficiency 65%. Throughout thesteady-state performance at an OLR of 2 g COD L1 d1 andprior to both perturbation periods, the ammonium, TSS and VSSconcentrations were around 2 g L1, 6 g L1, and 5 g L1, respec-tively. In addition...</p></li></ul>