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Many recent breakthroughs in our understanding of termite biology have been facilitated by “omics” research. Omic science seeks to collectively catalog, quantify, and characterize pools of biological molecules that translate into structure, function, and life processes of an organism. Biological molecules in this context include genomic DNA, messenger RNA, proteins, and other biochemicals. Other permutations of omics that apply to termites include sociogenomics, which seeks to define social life in molecular terms (e.g., behavior, sociality, physiology, symbiosis, etc.) and digestomics, which seeks to define the collective pool of host and symbiont genes that collaborate to achieve high-efficiency lignocellulose digestion in the termite gut. This review covers a wide spectrum of termite omic studies from the past 15 years. Topics covered include a summary of terminology, the various kinds of omic efforts that have been undertaken, what has been revealed, and to a degree, what the results mean. Although recent omic efforts have contributed to a better understanding of many facets of termite and symbiont biology, and have created important new resources for many species, significant knowledge gaps still remain. Crossing these gaps can best be done by applying new omic resources within multi-dimensional (i.e., functional, translational, and applied) research programs.
In a broad sense, the underlying goals of omic
Termite omic research has focused on the host termite, individual gut microbial symbionts or entire populations of gut microbes. In the latter case, these “meta” analyses focusing broadly on collective microbiota occurring in the gut microenvironment have been popular, particularly with microbiologists specializing in termite intestinal microbiology. Although it presents significant bioinformatic challenges, a more inclusive approach that considers host and symbionts together as a single functional unit is the best approach for appreciating the full functional capacity of termites. A fundamental advantage of omic research over more traditional organismal research is that it enables direct mechanistic insights into termite and symbiont physiology and biochemistry. The use of omic technologies has led to new insights into behavior, social structure, digestion, and host-symbiont/symbiont–symbiont interactions, and many other aspects of termite biology. However, also as addressed throughout this review, omic science has limits for being able to define biological function.
Termites are perhaps best know1n for their symbiotic associations with gut microbes (
The term
Based on a recent literature survey (
In total, 82 termite species have been investigated using various omic approaches, with greater representation by lower than higher termites (72 vs. 28%). Among lower termites the top genera studied are important pest groups (
Of the various omic studies to date considering symbiosis and symbiotic partnerships in termite systems, the majority have taken an exclusive symbiont-oriented approach (>60%), whereas a minority have considered the host termite separately (<20%). The remainder have considered host and symbiont together (∼20%). In the latter category of host and symbiont combined, some studies have been a case of “accidental metatranscriptomics” (because protist symbionts have polyadenylated transcripts that are represented in cDNA libraries along with host transcripts; e.g.,
In terms of experimental approaches taken, there has been an approximately equal split between descriptive and hypothesis-driven studies. Regarding the types of sequencing performed, transcriptomics and metatranscriptomics have been the dominant approaches (25 and 21% of studies), followed by microbial surveys for cataloging purposes (23%). The transcriptomic approaches used can be further divided into different methodologies such as cDNA library sequencing (Sanger, pyrosequencing or Illumina RNA-seq) and microarrays. Other efforts have targeted symbiont metagenomes (15%), symbiont or termite genomes (9%), proteomes (3%), and DNA methylomes (3%).
A comprehensive literature summary of termite omic research, organized by approaches taken.
Omic approach taken | Termite group | Termite species | Host or symbiont | Tissue or fraction | Approach | Method | Major finding | Reference |
---|---|---|---|---|---|---|---|---|
Transcriptome | Lower | Host | Whole-body polyphenic library | Hypothesis-driven (virgin vs. egg-laying queens) | Sanger sequencing + microarray | 7663 ESTs sequenced that aligned into 4726 contigs; microarray analysis revealed 94 differentially expressed genes between virgin and reproductive queens | ||
Combined | Whole workers | Hypothesis-driven | Sanger sequencing | 1511 total unigenes (362 contigs + 1149 singletons) | ||||
Host | Head tissue | Descriptive | Sanger sequencing | 3003 high quality ESTs were obtained that aligned into 695 unigenes (245 contigs and 450 singlets) | ||||
Combined | Whole workers and neotenic reproductives | Hypothesis-driven | Representational difference analysis, Sanger sequencing | 187 differentially expressed library clones were identified that aligned into 35 unigene contigs | ||||
Host | Head tissue of differentiated workers and soldiers | Hypothesis-driven | Differential display, Sanger sequencing | 11 candidate bands were identified, including the |
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Host | Mandibular tissue of workers, presoldiers, and soldiers | Hypothesis-driven (JHA induced gene expression) | Fluorescent differential display (FDD), Sanger sequencing | 81 candidate bands identified by FDD that aligned into 12 unigenes upregulated in mandibular tissue during soldier differentiation | ||||
Host | Whole worker termites without guts | Hypothesis-driven (JHA up and downregulated genes) | FDD, Sanger sequencing | 28 candidate bands identified by FDD; 18 aligned into ca. 5 unigenes | ||||
Host | Worker brain and subesophageal ganglion | Hypothesis-driven (JHA induced gene expression) | FDD, Sanger sequencing | No differences in expression patterns detected between pseudergates and soldiers; five genes up-regulated in brain and/or SOG during differentiation | ||||
Host | Whole worker termites without guts | Hypothesis-driven (JHA up and downregulated genes) | Subtractive libraries, filter arrays, and Sanger sequencing | 87 and 64 JHA up- and downregulated clones identified | ||||
Host | Worker head, thorax and front legs | Hypothesis-driven (genes upregulated by |
Subtractive cDNA library, Sanger sequencing | The number of differentially expressed clones was not specified | ||||
Combined | Whole worker termites | Hypothesis-driven | Sanger sequencing | 19 total unigenes (13 contigs + 6 singletons) | ||||
Multi-species: |
Combined | Whole workers and neotenic reproductives | Hypothesis-driven | Representational difference analysis, Sanger sequencing | 16 differentially expressed genes were identified in |
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Lower and higher | Multi-species: |
Host | Whole-body minus gut | Hypothesis-driven | 454 pyrosequencing | >1.2 million quality-filtered reads yielding >400 million bases for each of the three species. Caste transcriptomes compared by GO and orthology searches. Putative JH and caste differentiation genes annotated | ||
Higher | Symbiont | Fungal ectosymbiont ( |
Descriptive | Subtractive cDNA library, Sanger sequencing | 1,382 and 325 EST contigs were obtained for non-subtracted (lignocellulose fed) and subtracted (lignocellulose minus lab diet) cDNA libraries | |||
Host | Soldier frontal gland | Descriptive | 454 pyrosequencing | 50,290 sequence reads were assembled into 1111 contigs (774 unigenes) | ||||
Host | Head tissue | Descriptive | Illumina sequencing | 116,885 unigene sequences; 30,646 with significant identity | ||||
Species unknown | Symbiont | Fungal ectosymbiont of higher termite ( |
Descriptive | 454 pyrosequencing | 6494 candidate genes (3301 contigs + 3193 singletons) | |||
Proteome | Lower | Symbiont | Gut symbiota (bacteria, protist) | Descriptive | LC-MS/MS (ion trap) and 2-D PAGE | Tubulins proved to be the most suitable protein family with which to identify flagellate populations from hindgut samples | ||
Higher | Symbiont | Bacterial gut symbiota | Descriptive | LC-MS | 886 proteins identified, 197 with known enzymatic function; very few cellulases identified | |||
Higher and lower | Multi-species: 12 species (10 lower, 2 higher) | Host | Labial glands of workers and soldiers | Descriptive | N-terminal peptide sequencing (Edman degradation) | Endogenous (host) endoglucanase cellulases were identified in worker labial glands of all species | ||
Metatranscriptome, metagenome, and 16S pyrosequencing | Higher | Multi-species: |
Symbiont | Bacterial gut symbiota | Hypothesis-driven (differences between wood and dung feeders) | 454 pyrosequencing | Firmicutes and Spirochaetes dominated in |
|
Metatranscriptome and proteome | Lower | Combined | Worker termite gut and protist microbiota | Hypothesis-driven (comparison of cellulose vs. wood vs. lignin feeding) | 454 pyrosequencing + LC-MS proteomics | 347,798 sequence reads aligned into 97,254 singlets + 9553 differentially expressed contigs; proteome and transcriptome results showed congruence | ||
Metatranscriptome and proteome | Lower | Symbiont | Protist gut symbiota (hindgut lumen) | Descriptive | Sanger sequencing + proteomics | 910 total clones sequenced; 580 candidate genes identified | ||
Metatranscriptome | Lower | Combined | Whole workers, nymphs, soldiers, and alates | Descriptive | Sanger sequencing (normalized polyphenic library) | 25,939 candidate genes (16 691 contigs and 9248 singletons) | ||
Symbiont | Protist gut symbiota | Descriptive | 454 pyrosequencing | 75,122 candidate genes (2891 contigs + 72,231 singletons) | ||||
Combined | Worker termite gut (salivary gland, foregut, midgut, and hindgut) and protist microbiota | Descriptive | Sanger sequencing | Different compositions of expressed genes were identified across gut regions | ||||
Multi-species: |
Symbiont | Protist gut symbiota (hindgut lumen) | Hypothesis-driven | Sanger sequencing | 910, 920, 1056, 1021, and 868 clones sequenced from each taxon ( |
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Combined | Whole-body polyphenic library (non-normalized) | Descriptive | Sanger sequencing (random clones) | 88 random clones were sequenced that aligned into 49 unigene contigs | ||||
Combined | Whole-body polyphenic library (non-normalized) | Hypothesis-driven (worker vs. soldier) | Filter arrays, Sanger sequencing | 105 differentially expressed clones were identified that aligned into 34 unigene contigs | ||||
Combined | Whole-body polyphenic library (non-normalized) | Hypothesis-driven (worker vs. immature reproductive) | Filter arrays, Sanger sequencing | 68 differentially expressed clones were identified that aligned into 25 unigene contigs | ||||
Combined | Worker termite gut and protist microbiota | Hypothesis-driven | Sanger sequencing | 6555 total transcripts (3044 host, 3511 protist symbiont) | ||||
Combined | Whole-body polyphenic library (soldier, worker, alate, early and late larvae) | Hypothesis-driven (comparisons among castes) | Sanger sequencing (random clones) | 15,259 random clones sequenced representing 6991 total genes | ||||
Combined | Worker termite gut and protist microbiota | Hypothesis-driven (comparison of JH, soldier head extract, live soldiers, and reproductives) | Microarray | 543 total gut genes differentially expressed after 24-h exposures (151 host + 392 protist symbiont) | ||||
Combined | Worker termite gut and protist microbiota | Hypothesis-driven (comparison of wood and cellulose/paper feeding) | Microarray | 544 total gut genes differentially expressed after 7-days feeding periods (236 host + 301 protist symbiont) | ||||
Symbiont | Bacterial gut symbiota |
Hypothesis-driven (comparison of two |
Illumina sequencing | Total database size = 3,855,671 reads; 45% of reads were 16S and 23S rRNAs; >97% of all non-rRNA genes were unique | ||||
Metagenome and proteome | Higher | Symbiont | Bacterial gut symbiota (P3 luminal contents) | Descriptive | Sanger sequencing + 454 pyrosequencing + LC-MS proteomics | 12 bacterial phyla and 216 phylotypes identified; >71 Mb of DNA sequenced; ∼700 glycoside hydrolase domains corresponding to 45 different carbohydrate active enzymes were identified (including putative cellulases and hemicellulases) | ||
Metagenome and 16S survey | Higher | Symbiont | Bacterial gut symbiota | Descriptive | 454 pyrosequencing | 548,807 total sequence reads; no evidence of lignases; 205 total cellulase and hemicellulase genes annotated | ||
Metagenome | LOWER | Symbiont | Bacterial gut symbiota | Descriptive | Illumina |
316 candidate cellulase ORFs, 259 candidate hemicellulase ORFs, and 12 candidate pectinase ORFs | ||
Symbiont | Bacterial gut symbiota | Descriptive | Functional screening (beta glucosidase) + Sanger sequencing | 9 beta glucosidase positive clones were identified from GH1, GH3, and GH4 | ||||
Symbiont | Bacterial gut symbiota | Descriptive | Functional screening (beta glucosidase) + Sanger sequencing | 1 beta glucosidase positive clone was identified (GH1) | ||||
Symbiont | Bacterial gut symbiota | Descriptive | Functional screening (xylosidase) + Sanger sequencing | 1 putative endo-1,4-beta-xylanase was identified from GH11 | ||||
Higher | Symbiont | Bacterial gut symbiota | Descriptive | Functional screening (beta glucosidase) + Sanger sequencing | 1 beta glucosidase positive clones was identified and functionally expressed | |||
Symbiont | Bacterial gut symbiota | Descriptive | 454 pyrosequencing (bacterial fosmid libraries grown under selective conditions) | 13 positive clones identified encoding 1 xylanase and 12 beta-glucosidases | ||||
Symbiont | Bacterial gut symbiota | Descriptive | Functional screening (cellulase and xylanase) + Sanger sequencing | Fourteen independent active clones (2 cellulases and 12 xylanases) were obtained by functional screening (GHF 5,8,10,11) | ||||
Symbiont | Gut and fungal comb bacteria | Descriptive | 454 pyrosequencing | 1.46 Mbp of metagenome sequence | ||||
Symbiont | Bacterial gut symbiota | Descriptive | Functional screening (esterase)+ Sanger sequencing | 68 fosmid clones were identified with esterase activity, of which the 14 most active were sub cloned and sequenced | ||||
Symbiont | Bacterial gut symbiota | Descriptive | Functional screening (feruloyl “FAE” esterase) + Sanger sequencing | Seven FAE-positive fosmid clones were identified | ||||
Metabolome | Lower | Combined | Worker termite gut | Descriptive | Isotope-ratio mass spectrometry (IR-MS) | Localized the majority of glucose release from 13C-cellulose to the foregut region | ||
Combined | Worker termite gut | Descriptive | TMAH thermocemical lysis coupled with GC-MS | Results transformed the view of lignin degradation in the termite gut | ||||
Combined | Worker termite gut | Descriptive | TMAH thermocemical lysis coupled with CP-MAS-NMR spectroscopy, and Py-GC/MS | During gut passage the native lignin macromolecular assembly undergoes structural modification but with conservation of the abundant β- |
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Combined | Worker termite gut | Descriptive | TMAH thermocemical lysis coupled with GC-MS | Results suggest that the plant cell wall deconstruction process in |
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Higher And lower | Multi-species: eight species (seven lower, one higher) | Host | Labial glands of workers and soldiers | Descriptive | HPLC MALDI-TOF and GC-TOF-MS | Hydroquinone and other glucose and benzene-linked compounds identified in labial gland secretions of workers and soldiers | ||
Genome | Lower | Symbiont | Bacteroidales endosymbiont (phylotype CfPt1-2) of the cellulolytic protist |
Descriptive | Combination of Sanger and 454 pyrosequencing | 1,114,206 bp chromosome containing 758 putative protein-coding sequences, 38 transfer RNA genes, and 4 rRNA genes | ||
Symbiont | Blattabacterium bacterial endosymbiont | Descriptive | Illumina sequencing | 594 candidate genes identified (544 protein-coding + 40 RNA-coding) | ||||
Symbiont | Bacterial gut symbiont ( |
Descriptive | Combination of Illumina + 454 pyrosequencing | Genome contains 6,051 genes with 5,987 CDS; 64 structural RNAs were identified with the presence of one rRNA operon | ||||
Symbiont | Bacterial gut symbiont |
Descriptive | Combined Sanger, Illumina, and 454 pyrosequencing | 4,486,650 bp long genome containing 4,264 predicted genes (4,210 protein-coding, 54 RNAs) | ||||
Symbiont | Endomicrobia “TG-1” endosymbiont (phylotype Rs-D17) of the cellulolytic protist |
Descriptive | Combination of Sanger and 454 pyrosequencing | 1,125,857 bp chromosome encoding 761 putative protein-coding genes | ||||
Genome, transcriptome, and DNA methylome | Lower | Host | Worker, soldier, reproductive, larvae | Descriptive | Illumina + 454 pyrosequencing | 562 Mb genome sequenced with 98x coverage; 96 miRNA, and 17,737 protein coding genes were identified | ||
Genome, fungal symbiont genome, and gut microbial metagenome | Higher | Combined | Genomic DNA of |
Descriptive | Illumina sequencing | First sequencing of a tripartite symbiotic system; 1.3 Gb host genome, 84 Mb fungal symbiont genome; 816 Mb gut prokaryotic metagenomes; major emphasis on cellulose digestion; greatly reduced gut microbiome in queens relative to major workers and minor soldiers | ||
DNA methylome | Lower | Host | Workers, soldiers and nymphs | Descriptive | Methylation-targeted amplification fragment length polymorphism (AFLP) | Found evidence for DNA methylation, but no differences in methylation levels among castes | ||
Lower and higher | Multi-species: |
Host | Whole-body minus gut | Hypothesis-driven | 454 Pyrosequencing | >1.2 million filtered reads yielding >400 million bases for each of the three species. DNA methyltransferases putatively responsible for DNA methylation were represented in all three species | ||
Lower | Multi-species: |
Host | Whole-body polyphenic libraries | Descriptive | Sanger sequencing | Signatures of high DNA methylation levels exist in |
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18S sequencing | Lower | Multi-species: |
Symbiont | Protist gut symbiota | Descriptive | 454 pyrosequencing | Protist diversity estimated by 18S SSU sequencing is much higher than when estimated by protist morphology | |
Lower | Symbiont | Protist gut symbiota (single cell) | Descriptive | Sanger sequencing | Seven protists identified by rRNA sequence | |||
18S and bacterial 16S sequencing | Lower | Multi-species: 24 lower termites and three |
Symbiont | Protist and bacterial gut symbiota | Hypothesis-driven | 454 pyrosequencing | Although microbial communities are vertically inherited and codiversification with the host termite has had a prominent role in structuring symbiont communities, dispersal appears to have a larger role in community composition | |
16S sequencing | Lower | Symbiont (positions 27-1492) | Cuticular bacteria | Hypothesis-driven | Sanger sequencing | 25 total ribotypes detected (20 and 14 from simple and extended families) | ||
Symbiont (positions 27-1492) | Bacterial gut symbiota (whole gut) | Hypothesis-driven | Sanger sequencing | 1,876 total 16S reads that sorted into 213 bacteria ribotypes and 13 phyla | ||||
Multi-species: |
Symbiont (positions 27-1492) | Bacterial endosymbionts of protist gut symbionts | Descriptive | Sanger sequencing | Each protist morphotype harbored “Endomicrobia” from unique phylogenetic lineages | |||
Multi-species: |
Symbiont (positions 63-1492) | Spirochaete gut symbiota (whole gut) | Descriptive | Sanger sequencing | >21 new species of |
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Symbiont (entire SSU region) | Bacterial gut symbiota (hindgut lumen) | Descriptive | Sanger sequencing + ARDRA analysis | Six phyla and 261 species-level phylotypes estimated | ||||
Symbiont (V5–V6 region) | Bacterial gut symbiota (hindgut lumen) | Hypothesis-driven | 454 pyrosequencing | 475,980 total 16S reads that sort into eight major bacterial phyla and 4761 species-level phylotypes (5% divergence level) | ||||
Symbiont positions (27-1492) | Bacterial gut symbiota (midgut, protozoa, hindgut fluid and wall) | Descriptive | Sanger sequencing + T-RFLP analysis | 392 clones sequenced; seven major phyla and >200 species-level bacterial ribotypes identified | ||||
Symbiont (positions 563-1114) | Bacterial gut symbiota (whole gut) | Descriptive | Sanger sequencing | 1344 clones sequenced; 11 phyla and 268 species-level phylotypes identified | ||||
Symbiont (positions 27-1492) | Bacterial gut symbiota | Hypothesis-driven (effects of antibiotic rifampicin) | Sanger sequencing | Six and 17 species-level OTUs were identified for rifampin and control treatments ( |
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Higher | Symbiont (positions 21 or 27-907) | Whole gut | Descriptive | Sanger sequencing | >8 Phyla identified (species-level estimates not provided) | |||
Symbiont (positions 338-518) | Bacterial symbionts from gut regions, soil and mound | Hypothesis-driven | Sanger sequencing + DGGE | 212 total clones sequenced; 101 different species-level phylotypes identified | ||||
Multi-species: |
Symbiont (positions 27-1492) | Bacterial gut symbiota | Hypothesis-driven | Sanger sequencing | 100, 100 and 96 clones sequenced from each taxon; 151 different phylotypes identified | |||
Multi-species: | Symbiont (positions 341-806) | Bacterial gut symbiota | Descriptive | 454 pyrosequencing | Performed 16S sequencing on nine fungus-growing termite species from one geographic region of Ivory Coast; Identified 16 phyla and 42 genera total, with 11 genera occurring in all nine species | |||
Symbiont (V1–V2 and V8 regions) | Bacterial gut symbiota (P3 lumen) | Hypothesis-driven | 454 pyrosequencing | 2269 species-level OTUs of which 1617 and 652 were from the V1–V2 and V8 regions, respectively | ||||
Symbiont (V3–V4 region) | Bacterial gut symbiota (six whole gut regions) | Descriptive | 454 pyrosequencing | 3,200-26,000 16S reads per gut region (crop, midgut and paunch P1–P4) that sort into seven major bacterial phyla | ||||
Symbiont (positions 27-1390) | Bacterial gut symbiota (whole gut) | Hypothesis-driven | Sanger sequencing + T-RFLP analysis | 388 total clones sequenced; 10 major phyla identified; 31–43 species-level phylotypes | ||||
Symbiont (positions 1170-1492) | Bacterial gut symbiota | Hypothesis-driven (difference between grass and sugarcane feeding field colonies) | 454 pyrosequencing | 2274 and 2943 species-level OTUs sampled from sugarcane and grass feeding colonies (1% divergence level); nine major phyla sampled; Firmicutes and Bacteroidetes most common |
At present only two termite genome sequences are available (
The
The
Five individual symbiont genomes have been sequenced (
At the time of writing this article, at least 12 prokaryotic metagenomes had been partially sequenced (
Around 15 transcriptomic studies to date have focused on physiological processes or tissues in the host termite (
Because of the importance of juvenile hormone (JH) to soldier caste differentiation and the reliability of JH treatment for inducing soldier caste differentiation, continuing focus has been placed on this transition in hypothesis-driven studies that combine JH assays with transcriptomics (e.g.,
The immune response is another aspect of host termite physiology investigated through transcriptomics. Four studies have revealed responses to immune challenges by both stereotypical and unprecedented immune-responsive genes (
In addition to host-targeted studies noted above, other studies have considered symbiont or host-symbiont metatranscriptome composition (
One microarray study investigated gut metatranscriptome changes in responses to JH, primer pheromones and socio-environmental conditions, suggesting interesting linkages between gut symbiota and caste differentiation (
Proteomics (
Four studies to date have looked at methylation signatures across termite castes with somewhat differing results. A seminal study used a methylation-targeted amplification fragment length polymorphism (AFLP) approach in
A subsequent study was done
Finally, DNA methylation was assessed in
While it is clear that DNA methylation exists in termites, so-far inconclusive results have been obtained to suggest epigenetic caste regulation. As concluded previously in relation to genetic caste determination (
Metabolomic studies are useful for assessing
Other metabolomic studies have focused on lignocellulose digestion. One main question addressed has been:
Another aspect of termite metabolomic research considers cellulose digestion and relative contributions of host and symbiont to this process. A recent metabolomic study investigated
Bacterial 16S rRNA sequence surveys have been used extensively for cataloging bacteria and archaea (
In comparison to prokaryotic 16S surveys, comparatively few protist 18S SSU surveys have been conducted (
Termite omic research in the last 10–15 years has led to a new era of understanding for termite and symbiont biology. Omics has also enabled the development of new unparalleled resources (i.e., transcriptome, genome, proteome, metabolome, symbiont meta-omic, and symbiont rDNA) useful for moving ahead with targeted functional work. The stage is now set for making significant headway in many aspects of termite research, including, but not limited to digestion, symbiosis, caste differentiation, and social evolution. However, key needs and opportunities remain in specific areas that seem particularly relevant for filling in knowledge gaps and potentially leading to transformative, paradigm-shifting outcomes.
Having the
On the topic of proteomics, more studies are needed in species that have had genomes, transcriptomes, metagenomes, or metatranscriptomes sequenced. Combining proteomics with nucleic acid sequencing will better resolve gene prediction models and better test for congruency between transcription and translation profiles. On the topic of metabolomics, termite digestion remains an area much in need of metabolomic research focusing on how complex lignocellulose is broken down in termite guts and converted to energy. Also, tracking metabolites as they leave the gut and are utilized in the termite body would be very informative for testing hypotheses on the relative importance of nutrient flow into symbiont metabolic pathways.
On the topic of DNA methylomics, while it is now clear that DNA methylation happens in termites, so-far inconclusive results have been obtained regarding the role of DNA methylation in caste regulation.
Substantial opportunities and needs still remain for 16S and 18S rRNA-based symbiont cataloging. Protist 18S SSU cataloging capabilities in particular have recently been developed, and can continue to improve provided that several conditions are met, such as: (1) appropriate primers can be developed, (2) statistically sound sampling regimes can be developed at biologically relevant scales, (3) single-cell microbiology and other data sources can be integrated, and (4) appropriate analytical tools developed (
Finally, regarding prokaryotic 16S surveys, much has already been done, but an important gap in knowledge is the extent to which environment influences bacterial microbiota composition. This is important information for understanding differences in behavior and physiology across the geographic range for a termite species, as well as potentially for limiting the extent to which generalizations can be made about the relative importance of individual microbes or core microbiota in gut communities.
This review has covered many aspects related to outcomes, findings and trends resulting from termite omic research. To date, omic research in diverse termite species has provided key insights into caste differentiation, digestion, pathogen defense and microbiomes, and most recently has provided two termite genome sequences. Termite omics has also created important tools and resources for conducting targeted, functional, translational, and applied research. However, these resources have only received limited attention to date for asking hypothesis-driven questions to elucidate the functional and evolutionary significance for pools of identified genes, proteins, and microbes. In recent years sequencing has rapidly moved into the realm of super high-throughput, with accompanying assembly and analyses requiring proportional super-computing power and bioinformatics expertise, but only limited resolution of biology or function. Transitioning from research that produces lists of genes, proteins and microbes, to research that determines their functional significance, is where the most important challenges lie for the next phases of termite science.
The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Apologies are extended to investigators whose research could not be cited because of space limitations. The author thanks Priya Rajarapu, Brittany Peterson, and Andres Sandoval for manuscript review, Vera Tai for sharing prepublication data, as well as his collaborators and all members of his laboratory, past and present, for their contributions and input.
The singular term “omic" is used as an adjective in this review.
The plural term “omics" is used as a noun.