APPLIED AND ENVIRONMENTAL MICROBIOLOGY, Oct. 2011, p. 7000–7006 Vol. 77, No. 190099-2240/11/$12.00 doi:10.1128/AEM.05609-11Copyright © 2011, American Society for Microbiology. All Rights Reserved.

Biodiversity of Active and Inactive Bacteria in the Gut Flora ofWood-Feeding Huhu Beetle Larvae

(Prionoplus reticularis)�†Nicola M. Reid,* Sarah L. Addison, Lucy J. Macdonald, and Gareth Lloyd-Jones

Scion, Rotorua 3046, New Zealand

Received 25 May 2011/Accepted 5 August 2011

Huhu grubs (Prionoplus reticularis) are wood-feeding beetle larvae endemic to New Zealand and belonging tothe family Cerambycidae. Compared to the wood-feeding lower termites, very little is known about the diversityand activity of microorganisms associated with xylophagous cerambycid larvae. To address this, we usedpyrosequencing to evaluate the diversity of metabolically active and inactive bacteria in the huhu larval gut.Our estimate, that the gut harbors at least 1,800 phylotypes, is based on 33,420 sequences amplified fromgenomic DNA and reverse-transcribed RNA. Analysis of genomic DNA- and RNA-derived data sets revealedthat 71% of all phylotypes (representing 95% of all sequences) were metabolically active. Rare phylotypescontributed considerably to the richness of the community and were also largely metabolically active, indicat-ing their participation in digestive processes in the gut. The dominant families in the active community (RNAdata set) included Acidobacteriaceae (24.3%), Xanthomonadaceae (16.7%), Acetobacteraceae (15.8%), Burkhold-eriaceae (8.7%), and Enterobacteriaceae (4.1%). The most abundant phylotype comprised 14% of the activecommunity and affiliated with Dyella ginsengisoli (Gammaproteobacteria), suggesting that a Dyella-relatedorganism is a likely symbiont. This study provides new information on the diversity and activity of gut-associated microorganisms that are essential for the digestion of the nutritionally poor diet consumed bywood-feeding larvae. Many huhu gut phylotypes affiliated with insect symbionts or with bacteria present inacidic environments or associated with fungi.

The huhu beetle (Prionoplus reticularis), of the primitivesubfamily Prioninae within the Cerambycidae, is one of NewZealand’s largest and best known endemic beetles. Huhu lar-vae grow up to 70 mm long and are commonly found feedingin freshly fallen and rotting logs of native trees and exoticsoftwoods (Fig. 1A and B). Larvae develop initially in thesubcortical layer and excavate tunnels through to the less nu-tritious heartwood, accelerating the breakdown of logs to frass(6, 7, 22). Of all the New Zealand endemic beetle larvae, thehuhu is remarkable because its gut system is able to digestmany exotic as well as native tree species and can also bereared on an artificial sawdust diet (35). Huhu larvae are eatenby many birds and animals (22), as well as being a wild-fooddelicacy and part of the traditional Maori diet (28).

Like many Cerambycidae larvae, huhu larvae are xyloph-agous, feeding in the same piece of wood and digestinglignocellulosic biomass with the aid of symbiotic gut micro-organisms. Symbiotic gut associations, ranging from obligatemutualism to facultative parasitism, play important roles inhost nutrition. The symbionts of wood-feeding termites, in-cluding diverse termite-specific bacteria, are well recognized(30). However, the available information on symbiotic associ-ations of the 35,000 cerambycid species spread throughout the

world is ambiguous (18). Most studies focus on gut-associatedmicroorganisms of invasive wood borers. Culture-dependenttechniques have identified an abundance of Gammaproteobac-teria and Actinobacteria isolates (1, 5, 32). Culture-independenttechniques have revealed more diverse gut bacterial commu-nities, but these are based on low (�300) numbers of clonesequences (13, 15, 18, 37). Since the number of phylotypesdetected in a sample depends strongly on the number of se-quences analyzed, we generated large numbers of short se-quences from 16S amplicons using pyrosequencing. To identifythe active abundant, active rare, and inactive populations, wesequenced amplicons derived from the 16S rRNA gene and,separately, those derived from 16S rRNA, an approach dem-onstrated previously (12, 23). The 16S rRNA data set indicatedthe community of metabolically active bacteria, i.e., those withhigher ribosomal content. The inactive community, includingdormant or dead bacteria, was represented by members of the16S rRNA gene data set not represented in the 16S rRNA dataset. Pyrosequencing in conjunction with a comparison of 16SrRNA gene versus 16S rRNA-derived data sets revealed acomplex and active microbial community in the gut of thiswood-feeding beetle larva.

MATERIALS AND METHODS

Sample collection and wood and frass analysis. Huhu larvae (and accompa-nying decaying wood) were collected and bagged from a decaying Pinus radiatalog from Whakarewarewa Forest (38.5°13�S, 176°00�E) in the Bay of Plentyregion, North Island, New Zealand. Pinus radiata is the dominant plantationforest tree cultivated in New Zealand. Larval guts were removed within 48 h.Huhu larval frass and wood samples (taken adjacent to but not in contact withthe larvae) were also collected. The neutral monosaccharide composition of

* Corresponding author. Mailing address: Scion, Te Papa Tipu In-novation Park, 49 Sala Street, Private Bag 3020, Rotorua 3046, NewZealand. Phone: 64-7-3435899. Fax: 64-7-3480952. E-mail: nicki.reid@scionresearch.com.

† Supplemental material for this article may be found at http://aem.asm.org/.

� Published ahead of print on 12 August 2011.

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wood and frass samples was determined by gas chromatography of alditol ace-tates prepared by acid hydrolysis, reduction, and acetylation (20).

Gut homogenate preparation. Larvae were euthanized in 70% ethanol for 1min and rinsed in buffered salts solution (0.2 g K2HPO4, 0.1 g KH2PO4, 0.15 gKCl, and 0.15 g NaCl per liter). Huhu guts (2.1 g), from the anterior midgut tothe posterior hindgut, were excised from 6 larvae (6.2 g), transferred to sterilebuffered salts solution, and ground to a homogenous suspension with a steriletool. The gut content pH was measured in this fresh homogenate using pHindicator.

Nucleic acid extraction. DNA was extracted from approximately 0.25 g ofpooled gut homogenate using the ZR soil microbe DNA kit (Zymo Research,CA) and purified using the Wizard DNA cleanup system (Promega, WI). DNAquality was checked by agarose gel electrophoresis and the A260/280 ratio andquantified using PicoGreen dye (Invitrogen, CA) on a POLARstar galaxy fluo-rometer (BMG LabTech, Offenburg, Germany) using E. coli DNA (product no.D2001, 5 mg; Sigma) as a standard.

RNA was isolated by resuspending 0.25 g of pooled huhu gut homogenate in0.5 ml of 240 mM potassium phosphate buffer (pH 8.0) and 0.5 ml of phenol-chloroform-isoamyl alcohol (25:24:1). This suspension was transferred to beadbeater vials containing 0.5 g each of 0.1-mm and 0.3-mm silica-zirconium beadsand lysed by agitation in a FastPrep bead beating system (MP Biomedicals, CA)for 30 s at 5.5 m/s. RNA in the aqueous phase (obtained by centrifugation) waspurified following the RNA/DNA minikit protocols (Qiagen, Hilden, Germany).RNA quality was assessed by agarose gel electrophoresis and quantified usingRiboGreen dye (Invitrogen) on a POLARstar galaxy fluorometer.

Biochemical characterization of huhu gut homogenate. The substrate uptakeprofile of larval gut homogenate was determined using Biolog GN2 MicroPlates(Biolog, Inc., Hayward, CA). Huhu larval gut homogenate, 125 �l, adjusted to anoptical density at 600 nm (OD600) of 0.1 with buffered saline, was added to wellsof duplicate microplates, which were placed in sealed plastic bags and incubatedat 30°C. Color development was measured at 597 nm after 24 h (automatedmicroplate reader, BMG LabTech).

To assess nitrogen-fixing potential within the gut population, the homogenatewas grown on nitrogen-limited minimal medium containing 0.4 g KH2PO4, 0.1 gK2HPO4, 0.2 g MgSO4, 0.1 g NaCl, 10 mg FeCl3, 2 mg Na2MoO4, 9 g glucose, 50mg yeast extract, and 0.2 g NH4Cl, pH 7.2 � 0.1, per liter and an acetylenereduction assay was performed (43).

Quantitative PCR analyses. The abundance of bacterial and fungal small-subunit rRNA genes was estimated by quantitative PCR analysis using Eub338and Eub518 primers for bacteria and 5.8s and ITS1f for fungi (10). Bacterialquantitative PCR (qPCR) assays were conducted as described previously using aLightCycler instrument (Roche Applied Science, Basel, Switzerland), Light-Cycler software version 3.5, and PCR mix (33). The fungal qPCR conditions were95°C for 10 min and then 50 cycles of 95°C for 5 s, 55°C for 4 s, and 72°C for 12 s.Duplicate threshold cycle values were converted to copy numbers using a Phan-erochaete chrysosporium RP-78 genomic DNA calibration. All amplification ef-ficiencies were greater than 90%.

Bar-coded pyrosequencing. Extracted RNA was reverse transcribed intocDNA using SuperScript VILO (Invitrogen). A portion of the 16S small subunitribosomal gene was amplified from DNA or cDNA using the 27F (5�-AGAGTTTGATCCTGGCTCAG-3�) primer with the Roche 454 “A” pyrosequencing

adapter (5�-GCCTCCCTCGCGCCATCAG-3�) and a 4-bp barcode sequenceand the 337R (5�-GCTGCCTCCCGTAGGAGT-3�) primer (19) containing theRoche 454 “B” sequencing adapter (5�-GCCTTGCCAGCCCGCTCAG-3�). Theunique 4-bp barcode was included on the forward primer for sorting pooledDNA- and RNA-derived data sets. The high-performance liquid chromatogra-phy (HPLC)-purified primers were obtained from Sigma-Life Science (St. Louis,MO). PCRs (50 �l) on cDNA and extracted DNA used high-fidelity DNApolymerase (Roche) and a 3-min denaturation at 95°C, 25 cycles of 95°C for 1min, 60°C for 1 min, and 72°C for 1 min, and a 1-min final extension at 72°C.Amplicons were purified using the QIAquick PCR purification kit (Qiagen),eluted in 40 �l elution buffer, quantified using Quant-IT PicoGreen (Invitrogen),and pooled to an equimolar concentration. Pyrosequencing was performed witha Roche GS-FLX and standard protocols at the Otago high-throughput DNAsequencing unit, Dunedin, New Zealand.

Processing of pyrosequencing data. All pyrosequencing reads were initiallyscreened for quality and length of sequences. Sequences containing unascribednucleotides or less than 150 bp in length and not starting with the expected 5�primer sequence were removed. Reads were also end trimmed based on qualityscores with an accuracy threshold of 0.2% (25) using LUCY (3).

Taxonomic classification. Filtered sequences from the 16S rRNA gene (DNAdata set), the 16S rRNA-derived data set (RNA data set), and the total data set(DNA plus RNA data sets) were run against version 10 of the RDP databaseusing the Ribosomal Database Project (RDP) pipeline classification algo-rithm with a confidence score of �80 to align and provide taxonomic classi-fication (45) (accessed 23 August 2010). For comparison, raw sequences fromthe DNA and RNA data sets were run through the PANGEA pyrosequencingpipeline (17).

Phylotype (OTU) identification, diversity, and estimated richness. Column-formatted distance matrix input files (uncorrected, distance cutoff of 0.2, mini-mum sequence overlap of 2.5) were created using the RDP pipeline. Distancematrices were constructed using the dist.seqs function in MOTHUR, version1.12.3 (38). Sequences with 97% similarity were assigned to operational taxo-nomic units (OTUs) with a further neighbor-clustering algorithm. Rarefaction,Shannon’s diversity index values (H�), and Chao1 richness estimates were cal-culated in MOTHUR for total, DNA, and RNA data sets. Reference OTUs wereselected and ranked according to abundance using the get.oturep command. The30 most abundant OTUs in the total data set were phylogenetically identifiedusing Megablast within PANGEA.

Overlap and similarity analysis. To compare overlap (based on OTU com-position) between the DNA and RNA data sets, a group file was generated byassigning every sequence to either the DNA or RNA data set. We also comparedthe overlap between rare and abundant members of each data set by creatinganother group file and assigning sequences from the total data set as either rare(n � 10 [equivalent to 0.07% and 0.05% of the DNA and RNA data sets,respectively]) or abundant. The similarities between pairs of these sets werecompared using the qualitative and quantitative similarity indices in MOTHUR.Shared and unique OTUs are graphically represented in Venn diagrams. Theidentities (to family level) of the shared and unique sequences were obtainedusing the PANGEA output file 2.2 Megablast.

Nucleotide sequence accession number. The sequences obtained in this studywere deposited in the GenBank short-read archive, accession number SRA023754.1.

RESULTS

Microbial activity. The lignin content (38.7% � 0.2%[mean � standard deviation]) of frass was higher than that ofintact wood (30.6% � 0.4%) due to depletion of carbohy-drates; no evidence of lignin transformation was obtained.Frass deposited by huhu larvae had lower levels of glucose,galactose, and mannose than adjacent wood, indicating thathuhu larvae consumed wood carbohydrates in the Pinus radiatalog. The gut homogenate was slightly acidic (pH � 6.5). Assayswith Biolog GN2 microplates indicated metabolism of the sol-uble hexose sugar constituents of wood (glucose, galactose,and mannose), as well as trehalose (a disaccharide used forcarbon storage by fungi) and N-acetyl-D-glucosamine (themonomeric component of chitin from fungal cell walls). Nitrogen-fixing activity was inferred by a positive acetylene reduction

FIG. 1. Prionoplus reticularis larva in frass (A), underside of larva(B), and larval gut (C). Abbreviations: C, crop; M, midgut; H, hindgut.

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assay following incubation of the gut homogenate in nitrogen-free medium supplemented with glucose.

Quantitative PCR estimates of bacterial and fungal abun-dance. Bacterial- and fungal-specific qPCR assays showed thatbacteria were numerically dominant in the larval gut commu-nity at a 16S/fungal ITS ratio of 1,000:1. The number of bac-terial 16S rRNA gene copies per ng of DNA was 59,000 �17,680 for huhu gut samples (confidence interval calculatedwith a significance level of 5%).

454 pyrosequencing analysis. After quality filtering andtrimming of the pyrosequencing 16S amplicons, a total of33,420 sequences were identified from the pooled gut contentsof six huhu larvae. These sequences included 14,058 from theDNA data set and 19,362 from the RNA data set, with anaverage sequence length of 230 � 3 bp and an average qualityscore of �0.2% error probability per base.

Taxonomic classification. The RDP Classifier was used todetermine the highest resolution taxon levels (see Table S1 inthe supplemental material). There was a low incidence of se-quences unclassified at the phylum level (3.6%). In total, 11phyla were identified by RDP Classifier in the DNA data setand six in the RNA data set (Table 1). Proteobacteria domi-nated both RNA and DNA data sets, comprising �50% ofthe sequences. Alphaproteobacteria were more abundant thanGammaproteobacteria and Betaproteobacteria. Acidobacteria,Bacteroidetes, and Firmicutes were also abundant. Actinobacte-ria were dominant in the DNA data set (8.7%) but not in theRNA data set (1.4%). The DNA set contained sequencesfrom Cyanobacteria, Deinococcus-Thermus, Fusobacteria,Spirochaetes, and TM7 phyla that were not represented in theRNA data set. Within the Alphaproteobacteria, Acetobacter-aceae were very abundant in the RNA data set, comprising3,059 sequences (15.8%) of the total RNA data set; Acetobac-teraceae were less abundant in the DNA data set, with only 684sequences. The remaining alphaproteobacterial RNA data setsequences were classified into the following families: Rhodospi-rillaceae (499 RNA sequences), Beijerinckiaceae (349), Caulo-bacteraceae (236), Sphingomonadaceae (181), and Bradyrhizo-biaceae (135). The majority (�90%) of Betaproteobacteriasequences were classified as belonging to the genus Burkhold-

eria. The gammaproteobacterial sequences in the RNA dataset were distributed between two families, the Xanthomon-adaceae (3,228 RNA sequences) and the Enterobacteriaceae(802). The complete taxonomic data from RDP rRNA Classi-fier for each data set are shown in Table S2 in the supplemen-tal material.

Diversity estimates. Rarefaction analysis was carried out toestimate the depth of diversity of the data sets. Total speciesrichness (DNA plus RNA data set) was high, comprising 1,479observed OTUs at 97% similarity (see Table S3 in the supple-mental material). There were 790 and 1,018 observed OTUs inthe DNA and RNA data sets, respectively. Chao1 richnessestimates suggest that approximately 75% of the estimateddiversity in these data sets was captured by our sequencing.Further sequencing would likely yield additional uniqueOTUs. Shannon indices calculated using normalized data setsgave very similar results (DNA � 6.09 and RNA � 6.03),suggesting that differences in richness were probably due to thelarger size of the RNA data set.

Abundance classification. The most abundant families in theRNA data set are given in Table 2. The 30 most abundantOTUs from the total data set (RNA data set plus DNA dataset) were identified, and a representative sequence for eachwas assigned a putative identity. Phylogenetic assignation ofthe 30 most abundant OTUs is given in Table 3.

The DNA and RNA data sets were split into four groups,abundant DNA (DNAabd), rare DNA (DNArare), RNAabd,and RNArare, at cutoffs of �10 sequences (abundant) and �10sequences (rare). The number of abundant OTUs was 345,representing 30,026 sequences, and the number of rare OTUswas 1,134, representing 3,394 sequences.

Overlap and similarity estimates. The overlap of OTUsamong groups as represented by Jaccard (similarity in commu-nity membership) and Yue-Clayton (similarity of communitystructure, �YC) estimators at 97% sequence similarity are pre-sented in Table 4. The highest similarity indices were amongDNAabd and RNAabd. The rare groups were the least similar inboth community membership and structure.

Venn diagrams (Fig. 2) illustrate OTU overlap betweengroups, as well as unique OTUs. Overall, 30% of OTUs wereshared between the DNA and RNA data sets. These 449shared OTUs represented the majority of sequences (28,999sequences, or 87% of the total data set) (Fig. 2A). Predictably,

TABLE 1. Phylum classificationa showing the numbers of sequencesin DNA and RNA data sets

PhylumNo. of sequences in:

DNA data set RNA data set

Proteobacteria 7,217 12,152Acidobacteria 2,317 4,704Bacteroidetes 1,544 1,018Actinobacteria 1,226 280Firmicutes 748 693Unclassified bacteria 726 498TM7 131 0Spirochaetes 58 0Cyanobacteria 48 0Planctomycetes 30 17Deinococcus-Thermus 9 0Fusobacteria 4 0

Total 14,058 19,362

a RDP Classifier with confidence threshold of 80%.

TABLE 2. Abundance ranking of top 10 families in RNA data set

Family

Sequences in RNAdata set(RDP)

Sequences in RNAdata set

(PANGEA)

No. % No. %

Acidobacteriaceae 4,704 24.3 3,317 19.9Xanthomonadaceae 3,228 16.7 3,244 19.5Acetobacteraceae 3,059 15.8 2,908 17.5Burkholderiaceae 1,668 8.7 1,647 9.9Enterobacteriaceae 802 4.1 819 4.9Rhodospirillaceae 499 2.6 552 3.3Sphingobacteriaceae 620 3.2 551 3.3Paenibacillaceae 156 0.8 531 3.2Beijerinckiaceae 349 1.8 450 2.7Caulobacteraceae 236 1.2 264 1.6

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most of the OTUs classified as abundant are shared (Fig. 2B).The majority of unique OTUs (RNA � 97%, DNA � 88%)were classified as rare (Fig. 2C).

Of the abundant OTUs, 86% (representing 28,320 se-quences) were in the RNAabd group, indicating that the ma-jority were metabolically active (Fig. 2B). Of the rare OTUs,68% (representing 2,250 sequences) were in the RNArare

group and therefore active (Fig. 2C).Reference sequences were obtained using MOTHUR and

identified by their corresponding Megablast file to identifywhich classes were shared among groups and which wereunique (see Tables S4 and S5 in the supplemental material). Inboth abundant and rare groups, the majority (�70%) of shared

sequences were found in the same seven classes, Acidobacteria,Actinobacteria, Alphaproteobacteria, Betaproteobacteria, Gam-maproteobacteria, Bacilli, and Sphingobacteria. Among the raregroups, Bacteroidia, Clostridia, and Deltaproteobacteria werealso prominent (see Table S5 in the supplemental material) inboth RNA and DNA data sets, but many of the OTUs withinthese classes were not shared.

The huhu larval gut data set (see Table S2 in the supple-mental material) was dominated by aerobic and facultativemicroorganisms. Strict anaerobes active in the gut includedonly a few clostridia (50 RNA sequences) and Deltaproteobac-teria of the order Desulfuromonadales (3 RNA sequences).Many other sequences currently unclassified beyond the orderlevel (33% could not be classified at order level) may representanaerobic bacteria, but this cannot be determined from currentanalyses.

DISCUSSION

Community differences. A large proportion (71%, repre-senting 95% of sequences) of OTUs were active within oursampled huhu larval guts (Fig. 2A). Among these, many (68%)of the rare OTUs were active (Fig. 2C). These results concurwith a study on a productive lake ecosystem that shows many

TABLE 4. Similarity indices for the DNA and RNA data sets andrare and abundant OTUs at 97% similarity

ComparisonCommunitymembership(Jaccard)a

Communitystructure

(�YC)a

% of sharedOTUs

% ofshared

sequences

DNA, RNA 0.30 0.49 (0.47–0.52) 30.4 86.8DNAabd, RNAabd 0.79 0.50 (0.48–0.53) 79.4 93.3DNArare, RNArare 0.15 0.09 (0.08–0.11) 15.4 28.9

a Estimators are scored on a scale of 0 to 1, with a score of 0 representingcomplete dissimilarity and a score of 1 representing identity.

TABLE 3. The 30 most abundant OTUs in the total data set

Rank OTUaHitsto

DNA

Hitsto

RNABacterial divisionb Closest Genbank sequence

(PANGEA)bBit

score%

identity Environment or characteristicc

1 3 779 2772 Gammaproteobacteria Dyella ginsengisoli 305 99.4 Soil2 36 420 659 Acidobacteria Acidobacterium capsulatum 327 93.1 Soil, termite, cerambycid3 12 338 724 Betaproteobacteria Burkholderia sp. PSB10 363 96.7 Forest soil, acid tolerance4 85 336 686 Acidobacteria Acidobacteriaceae Ellin5095 420 96.4 Forest soil, acidic peat bog5 120 368 330 Firmicutes Paenibacillus sp. GP26-03 363 94.1 Rhizoplane, zebrafish gut6 116 107 505 Acidobacteria Acidobacteria Ellin7225 402 96.2 Soil7 5 43 558 Alphaproteobacteria Rhodospirillales Ellin5134 307 93.4 Forest soil, acidic river8 43 352 231 Bacteroidetes Bacteroidetes bacterium 0-9 239 96.7 Soil, leaf litter9 17 26 518 Gammaproteobacteria Enterobacteriaceae M528 313 99.4 Pine beetle gut10 113 331 199 Alphaproteobacteria Beijerinckiaceae BW872 456 100 Forest soil, cerambycid gut

11 71 104 313 Acidobacteria Acidobacteria Ellin7171 444 99.1 Forest soil, acidic peat bog12 162 197 196 Acidobacteria Acidobacteriaceae Ellin633 412 97.8 Soil13 64 370 10 Alphaproteobacteria Novosphingobium nitrogenifigens 466 100 High C:N wastewater14 40 371 0 Actinobacteria Cellulosimicrobium cellulans 436 98.315 131 356 13 Gammaproteobacteria Gammaproteobacterium PG11/37 343 100 Acid forest soil, cellulolytic16 73 155 190 Betaproteobacteria Burkholderia sordidicola 377 96.8 White-rot fungus, soil17 191 252 81 Alphaproteobacteria Bradyrhizobium bacterium RCO 389 10018 35 65 261 Alphaproteobacteria Azospirillum brasilense 327 92.2 Acid tolerance19 250 119 187 Acidobacteria Acidobacteria Ellin7225 426 97.5 Forest soil20 38 83 213 Acidobacteria Acidobacteriaceae TAA166 420 98.3 Termite gut, forest soil

21 21 23 256 Alphaproteobacteria Acetobacteraceae Ellin5134 359 94.5 Soil, acidic river22 97 108 162 Alphaproteobacteria Acidisphaera sp. NO-15 301 93.8 Soil, wastewater, acid23 75 129 137 Betaproteobacteria Burkholderia bryophila 313 95.0 Fungi24 111 60 206 Alphaproteobacteria Acetobacteraceae bacterium PN29 351 94.425 18 79 185 Alphaproteobacteria Acidocella sp. NO-12 311 92.926 101 59 201 Gammaproteobacteria Bacterium Ellin5260 258 96.127 80 176 83 Alphaproteobacteria Methylocapsa sp. KYG 398 96.6 Gold, coal mine soils28 53 69 190 Gammaproteobacteria Bacterium Ellin5264 408 95.929 15 78 168 Acidobacteria Acidobacterium sp. Ellin457 373 99.5 Soil30 81 243 0 Actinobacteria Blastococcus saxobsidens 460 100 Termite mound

a Refers to each OTU’s identifier within the total data set.b Designations assigned by PANGEA Megablast output file 2.2.c From Greengenes (http://greengenes.lbl.gov).

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rare bacterial phylotypes are active (23) but differ from a studyof coral reef sediment that showed a predominantly inactiverare bacterial community (12). The composition of the activerare and active abundant communities was similar at the classlevel (see Tables S4 and S5 in the supplemental material). Theactive rare community contributed substantially to overall rich-ness (52% of all OTUs), highlighting the capability of rare taxato contribute to digestion processes in huhu larvae.

Of the abundant RNA sequences that were absent from theDNA data set, 67% belonged to the family Acetobacteraceaewithin the Alphaproteobacteria and included affiliations withthe genera Acidocella, Acidisphaera, and Acidisoma, as well asmany (2,594 sequences) unclassified Acetobacteraceae. An el-evated frequency of RNA compared to DNA transcripts mayindicate slow-growing organisms with disproportionately highmetabolic activity (29). Members of the genus Acidocella areknown slow growers (11). Bacteria such as these would beunderrepresented (or absent) in data generated only from the16S rRNA gene.

Metabolically inactive representatives were dominated byActinobacteria. Actinobacteria sequences made up 8.7% of theDNA data set, with 22 genera, but only 1.4% of the RNA dataset. Actinobacteria are commonly isolated from insect guts (13,15, 18, 24) and often identified as defensive mutualists (39),although a role in hemicellulose degradation among ceramby-cid beetles has been suggested (32). Recently, it has beenshown that Actinobacteria increasingly dominate in later stagesof forest litter decomposition (42). The log sampled in thisstudy may not have decayed sufficiently to benefit this group ofbacteria, resulting in their lower than expected metabolic ac-tivity.

Community composition and richness. The distribution ofsequences among phyla is broadly consistent with sequencedata from clone libraries constructed from the cerambycidlarvae of the Asian longhorned beetle (15) and Leptura rubra(18), with the exception that Alphaproteobacteria were moredominant than Gammaproteobacteria in our data set. Highabundances of Alphaproteobacteria and Acidobacteria havebeen described in acid forest soils (47) and a decayed woodsample inhabited by white-rot fungi (44). Enterobacteriaceaemade up a smaller component (RNA 4%, DNA 0.3%) of huhugut sequences than reported by culture-based approaches withother insect species (5, 15, 16), probably due to culture condi-tions that favor Enterobacteriaceae.

We obtained similar estimates of alpha diversity using bothPANGEA and RDP/MOTHUR. As is common with large data

sets, rarefaction analysis indicated that we have not surveyedthe full extent of bacterial diversity within the huhu larval gut.Chao1 index results suggest that the gut of the huhu larvaharbors more than 1,800 bacterial OTUs (based on 95% lowerconfidence interval at 97% similarity, DNA plus RNA dataset), less than the 4,500 per marine sponge (46) and more thanthe 100 to 500 in termite guts (based on Chao1 at 97% simi-larity) (21). Much less diversity (20 to 60 OTUs) has beendescribed for cerambycid larvae (1, 5, 13, 14, 18, 32, 37), albeitat a coarser level of analysis.

Identity and activity of abundant OTUs. The prevalent phy-lotype, OTU 3 (2,772 RNA sequences) matched Dyella ginsen-gisoli (99% similarity). Dyella species (Xanthomonadaceae)have been isolated from many soils, and recently, a Dyellaspecies exhibiting cellulase activity was isolated from the gut ofa lower termite (2). Dyella ginsengisoli LA-4 degrades a varietyof aromatic compounds, including biphenyls (27). Their dom-inance in our data sets suggests a role in the metabolism oflignin-derived aromatic compounds; however, more work isrequired to test this hypothesis. Another dominant phylotype,OTU 17 (518 RNA sequences), showed high similarity toEnterobacteriaceae, particularly clones isolated from the gutof larval and adult southern pine beetles, Dendroctonus fron-talis. A dominant alphaproteobacterial phylotype, OTU 113(Table 3), closely matched an uncultured bacterium isolatedfrom the digestive system of the cerambycid beetle Lepturarubra (18).

The OTUs we assigned to Acetobacteraceae all had very lowsimilarity (�95%) to their closest relative, and none wereaffiliated with an insect symbiont. Acetobacteraceae have beenidentified as secondary symbionts of insects dependent onsugar-based diets and are implicated in many aspects of hostbiology (4).

In the DNA and RNA data sets, 969 and 1,668 sequences,respectively, were classified as Burkholderia. Many had bestmatches with species associated with (i) fungi or endosymbi-onts in ectomycorrhizal fungi, (ii) insects, and (iii) environ-mental sequences from forest soils. A Burkholderia isolate hasbeen obtained from a cerambycid beetle (31), which supportsthe possible association of this genus with huhu larvae reportedhere. A symbiotic relationship between fungi and Burkholderiahas been suggested whereby the bacteria utilize aromatic com-pounds liberated by the degradation of lignin by white-rotfungi (40). Other putative functions for Burkholderia includenitrogen fixation (9), defense mechanisms (36), aromatic com-

FIG. 2. Venn diagrams showing overlaps of OTUs (at 97% similarity) and sequences. Values are the numbers of OTUs calculated using thetotal data set. Rare, n � 10; abd (abundant), n � 10.

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pound degradation (26), and detoxification of tree defensecompounds (41).

The Acidobacteria are highly represented in the active pop-ulation (4,704 RNA sequences). Cultured Acidobacteria iso-lates can utilize plant polymers, including xylan and cellulose(8), and it is tempting to speculate that Acidobacteria partici-pate in the degradation of these polymers in the larval gut.Acidobacteria clones were identified from the larvae of thecerambycid Leptura rubra feeding on rotten softwood (18). Thesecond most dominant phylotype, OTU 36 (659 RNA se-quences), closely matched an uncultured Acidobacteria clonefrom L. rubra (96% identity), and both OTU 36 and OTU 38(213 RNA sequences) matched with Acidobacteria termite gutclones.

Within the phylum Bacteroidetes, class Sphingobacteria, thefamily Sphingobacteriaceae was well represented (1,018 RNAsequences). A Sphingobacterium isolate exhibiting xylanolyticactivity has been isolated from the gut of a cerambycid larva(48).

Many of the Firmicute sequences belonged to unclassifiedBacillales (350 RNA sequences), Paenibacillaceae (156 RNAsequences), or Carnobacteriaceae (104 RNA sequences). OTU120, the 5th most abundant phylotype in the data set, had lowidentity to a Paenibacillus species isolated from zebrafish gut.

Many of the above-mentioned families contain nitrogen-fixing bacteria. These have previously been identified in guts ofwood-feeding insects (34). Nitrogen fixation activity (asmeasured by acetylene reduction) was detected in huhu guthomogenate, and many phylotypes identified in this study couldcontribute to this activity.

Affiliations with acidic environments, fungi, and other asso-ciations. Numerous sequences identified in our study wereaffiliated with clones or isolates that were acidophilic or iso-lated from acidic environments. Acidic conditions in the huhugut may result from fermentation of sugars to short-chain fattyacids and/or fungal exudation of strong organic acids, e.g.,oxalic and citric acids. The fungal/bacterial ratio in huhu larvalguts was higher than in other xylophagous insect guts (N. M.Reid, unpublished data); fungi in the huhu gut probablyinfluence the bacterial community composition. Bacteriawith known fungal associations and the ability to grow onfungal metabolites or biopolymers (such as chitin) were prev-alent in our huhu gut data sets. Many sequences were affiliatedwith isolates that demonstrated hemicellulase and cellulaseactivity or can utilize aromatic compounds from lignin degra-dation by fungi. Further investigations are required to definethese fungal-bacterial interactions.

The bacterial taxonomic composition in our huhu larval gutsresembles a community coexisting with a white-rot fungus indecayed wood (44). Huhu larvae are versatile wood feeders,consuming a variety of tree types in different states of decay,and even sawdust free of fungi (35). In this study, we havetaken a snapshot of the metabolically active gut bacteria fromhuhu larvae living in a decayed Pinus radiata log. Furtherresearch is necessary to identify the frequency of association ofthese phylotypes with guts of huhu larvae growing on differingwood diets and under various decay states, as well as identify-ing their physiological roles in the gut.

ACKNOWLEDGMENTS

We acknowledge Kirk Torr for analysis of wood and frass samplesand Joseph Dubouzet and Mark West for helpful comments duringmanuscript preparation.

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