Macrostomum lignano. We used a state-of-the-art toolbox to identify the involved adhesive and release molecules. We aim for understanding the fundamental mechanisms that mediate adhesion and release in flatworms, with the future goal of generating a flatworm-derived biomimetic glue that can be applied in biomedicine and industry.Synthetic adhesives are widely used in our daily lives, in medicine and industry. These man-made glues contain toxic or carcinogenic components. In contrast, biological adhesives produced by animals and plants are nontoxic and tissue-compatible, and are able to function under wet conditions. However, little is known about the mechanisms underlying biological adhesives. We characterized adhesion and release in our model system  Macrostomum lignano features a duo-gland adhesive system that allows it to repeatedly attach to and release from substrates in seawater within a minute. However, little is known about the molecules involved in this temporary adhesion. In this study, we show that the attachment of M. lignano relies on the secretion of two large adhesive proteins, M. lignano adhesion protein 1 (Mlig-ap1) and Mlig-ap2. We revealed that both proteins are expressed in the adhesive gland cells and that their distribution within the adhesive footprints was spatially restricted. RNA interference knockdown experiments demonstrated the essential function of these two proteins in flatworm adhesion. Negatively charged modified sugars in the surrounding water inhibited flatworm attachment, while positively charged molecules impeded detachment. In addition, we found that M. lignano could not adhere to strongly hydrated surfaces. We propose an attachment–release model where Mlig-ap2 attaches to the substrate and Mlig-ap1 exhibits a cohesive function. A small negatively charged molecule is secreted that interferes with Mlig-ap1, inducing detachment. These findings are of relevance for fundamental adhesion science and efforts to mitigate biofouling. Further, this model of flatworm temporary adhesion may serve as the starting point for the development of synthetic reversible adhesion systems for medicinal and industrial applications.The flatworm  Bioadhesion is the attachment of an organism to a surface using natural macromolecules. An increasing number of studies have focused on the investigation of marine biological adhesives and the development of biomimetic counterparts –3. Bioad81215Macrostomum lignano, lives between the sand granules of the intertidal zone. In its natural environment, M. lignano can attach and release several times to any substrate within a single minute , and transgenesis  and Mlig-ap2, comprising 5,407 and 14,794 amino acids, respectively. Mlig-ap1 and Mlig-ap2 transcripts were expressed in cells located in the flatworm tail  at the N- and C-terminal ends, together comprising more than 3,600 amino acids. These regions were extremely positively charged, with an isoelectric point of 14.43 (KR-region A), 14.54 (KR-region B), and 14.62 (KR-region C). Several domains were present in the middle portion of Mlig-ap1, including a C-type lectin-binding domain, a von Willebrand factor D domain , and a fibrillin-like region containing a series of 17 EGF-like calcium-binding modules .We have identified two large adhesive proteins, orm tail A–G. Douborm tail H–J. A se modules K. The Ml modules K comprisM. lignano  and four were part of Mlig-ap2 .Two previous in situ hybridization screens of tail-specific transcripts of  lignano , 24 reve lignano  were exp lignano , 24. Bas lignano , 25, we n = 3) and showed that the PNA target sugar Gal-β(1–3)-GalNAc was part of the Mlig-ap2 glycosylation. Multiple peptides of Mlig-ap2 were found by mass spectrometry in each experiment (Dataset S1). Two control pull-downs with PNA preincubated with its inhibitory monosaccharide d-galactose proved the specificity of the pull-down, since no or only one peptide was found in the eluates (Dataset S1). Additional whole-mount staining with PNA compared with control staining with blocked PNA showed that all labeling in the head and tail was gone when PNA was inhibited with d-galactose   but not in anchor cells . We generated multiple Mlig-ap1– and Mlig-ap2–specific antibodies  and corroborated their expression in the adhesive gland cells . In summary, the expression data confirm the localization of both mRNAs and proteins in the adhesive gland cells.Next, we confirmed that adhesive secreting cells in the flatworm tail contained Mlig-ap1 and Mlig-ap2. In a previous study, we showed that peanut agglutinin-lectin (lectin PNA) was an adhesive gland cell marker . Howeveror cells , 29 (SI Movie S1), the flatworms left footprints of Mlig-ap1 and Mlig-ap2 on the surface . In contrast, Mlig-ap2 accumulated mostly in the center of the adhesive papillae (Insets). Scanning electron microscopy and transmission electron microscopy corroborated the shape of the adhesive footprint .Next, we explored whether the flatworms secreted these adhesive proteins when they attached to a substrate. During attachment . Likewise, the same protein regions were identified in amputated tail samples, which were processed for mass spectrometry (Dataset S3). However, the extremely high lysine and arginine content of Mlig-ap1 hindered the generation of suitable peptides (trypsin cuts at lysine and arginine amino acids) for mass spectrometry . The protein regions identified by the mass spectrometry of the amputated tails were similar to the peptides identified in the adhesive footprints. Therefore, we conclude that both adhesive proteins were secreted and participated in the attachment.The presence of Mlig-ap1 and Mlig-ap2 in the adhesive footprints was further corroborated using mass spectrometry. To maximize the number of peptides available for mass spectrometry, proteases  were applied in independent experiments together with deglycosylation of proteins. Multiple peptides of both adhesive proteins were identified  (Movie S2).We performed functional analyses by RNAi to assess the involvement of Mlig-ap1 and Mlig-ap2 in achieved , 34  af afM. ligMlig-ap1 expression (Mlig-ap2 mRNA levels (Movie S3).RNAi knockdown of Mlig-ap1 during the 9 d of tail-plate regeneration resulted in a significant reduction of pression E, while A levels F and PNAA levels G were noA levels H. In theMlig-ap2 showed no effect on Mlig-ap1 expression (Mlig-ap2 mRNA (n = 40) (Movie S4). Notably, no Mlig-ap1 footprints were present after Mlig-ap2 RNAi. These findings suggest that Mlig-ap1 had no or only weak interaction with the surface and that Mlig-ap1 alone was not sufficient for animal attachment. The same results were obtained with a double-RNAi experiment of Mlig-ap1 and Mlig-ap2 (Movie S5). At the ultrastructural level, double knockdown resulted in a complete loss of adhesive vesicles . In summary, RNAi experiments confirmed that both proteins exhibit a spatially restricted distribution within the adhesive vesicles and that they play an essential role in M. lignano adhesion.RNAi knockdown of pression I but ledap2 mRNA J, a lackap2 mRNA K, and adap2 mRNA L. The knvesicles P. FurtheM. lignano attachment or release process . First, we wanted to exhaust the flatworm’s attachment capacity by manually pipetting or by keeping the flatworms on a horizontal shaker for up to 24 h. We found no reduction in attachment capacity. Instead, the animal sequentially used different adhesive organs (Movie S6). We hypothesize that they recharged the tip of the gland cell necks with new adhesive vesicles. Accordingly, the ultrastructure of the adhesive gland cell necks of animals that were manually pipetted for 5 min showed a significantly reduced number of adhesive vesicles in some of the adhesive gland cells .We tested various conditions that might interfere with the SI Appendix, Fig. S15).Next, we changed the parameters of the culture medium with respect to salinity (2 to 60 ppm), pH (pH 4 to 10), and temperature (10 to 32 °C). None of these changes disrupted the flatworms’ ability to attach and release  have been used frequently as model surfaces in bioadhesion and biofouling research, for example to test the attachment of bacteria, algal spores, and proteins –39. We tSI Appendix, Fig. S16). These results indicated that flatworm adhesion was not possible on highly hydrated surfaces. We expect that on regular surfaces, Mlig-ap2 displaced water to directly interact with the substrate surface for attachment. On highly hydrated surfaces, however, the water molecules cannot be displaced, and the interaction of Mlig-ap2 with the surface was impeded. Direct demonstration of the displacement of interfacial water during attachment is a considerable experimental challenge and currently not feasible due to spatial and temporal limits of available methods.We then tested surfaces with gradually reduced hydration. We use the term “hydration” for hydrophilic surfaces with different levels of internal hydration. We generated oligo(ethylene glycol)-terminated alkanethiol-coated surfaces with six, four, two, and one ethylene glycol units . While the contact angles of the EG1 to 6 surfaces were comparable, the internal hydration of the EGx chains was different . Various concentrations of glucose, galactose, or lectin PNA had no effect on flatworm attachment and release . Notably, only Mlig-ap2 footprints were found, while Mlig-ap1 was missing . These observations demonstrated that negatively charged molecules impair flatworm attachment. From those observations, we propose that heparin or Fondaparinux adsorbed to the positively charged Mlig-ap1 when it was released from the vesicles, preventing the cohesive function of Mlig-ap1. We predict that a small negatively charged molecule served as a releasing factor in M. lignano.We next investigated whether carbohydrates played a role in the attachment or release process. Remarkably, 2% heparin in artificial sea water (ASW) completely inhibited attachment A. Howeve missing B, 1. Lik missing B, 2. The missing B, 1 pres missing A. Likewi missing B, 1. How2 in H2O). The flatworms were able to attach at all concentrations. However, they were unable to detach from 80 to 100% of 7.14% MgCl2 (Movie S7). In contrast, all worms in regular ASW detached within 30 s. In a separate experiment, the presence of 1-phenoxy-2-propanol (0.1% in ASW), a common muscle relaxant, inhibited muscle contraction but did not alter the adhesion or releasing process (Movie S8). This finding suggests that muscle contraction was not involved in M. lignano attachment or release. Next, we assumed that the presence of positively charged ions might affect the releasing process. To further evaluate this hypothesis, we tested l-lysine– and arginine-monohydrochloride solutions (10% in ASW). The flatworms moved and behaved normally, but once they attached to the substrate, 70% (n = 10) of the animals could not release (Movie S9). When the positively charged peptide used for antibody production (SRKPRRKNRKSRKP) was added to the culture medium (4 mg/100 µL), detachment was also impaired. These findings indicate that positively charged molecules interfere with the flatworm detachment process.Next, we replaced the culture medium (ASW) with variable concentrations of isoosmolar magnesium chloride  in the medium hindered flatworm detachment , and element analysis revealed a low density of proteins in the releasing vesicles .This model is supported by the observations that negatively charged carbohydrates bound to the positively charged lysine and arginine repeats of Mlig-ap1, inhibited its cohesive function, and, consequently, the attachment A. In contachment B. AdditiUnderstanding the mechanisms involved in biological adhesion is important for interfacial chemistry, biofouling, and biomedicine, including the development of novel biomimetic glues. An increased knowledge of the fundamental mechanisms of bioadhesion and the related macromolecules is crucial for the development of next-generation adhesives that can rapidly adhere in wet environments and have a reversible adhesive capacity.M. lignano. We identified only two adhesive proteins in M. lignano, and no other candidates have been found in previous studies   and the nt of 5% , while tnt of 5% .The role of glycosylation in bioadhesion is not well-understood, even though it is commonly found in marine bioadhesives. We have confirmed that the sugar Gal-β(1–3)-GalNAc is associated with Mlig-ap2. Glycosylation has been shown to be involved in the adhesion of limpets, mussels, barnacles, algae, and sea stars –49. ThesLeptasterias hexactis , which strongly reacted to the flatworm’s glycocalyx  was not possible, while footprints could be detected on the less hydrated EG1 SAM. Previous experiments  and four  belonged to Mlig-ap2 . Full-length Mlig-ap1 is part of the genomic contig scaf1170 of the Mlig_3_7 genome assembly . Full-length Mlig-ap2 is part of the genomic contig scaf3366 of the Mlig_3_7 genome assembly . We corroborated the expression patterns and confirm that all transcripts show expression in the tail . The isoelectric point of Mlig-ap1 was determined using Isoelectric Point Calculator software , and Mlig_RNA_3_7_DV.v1 . Obtained fragments were cloned in pGEM-T (Promega) and sequenced by Microsynth.Sequences from the transcriptomes MLRNA110815 , MLRNA13_7_DV.v1  and geno_7_DV.v1  and Mlig_7_DV.v1  were usez-projected.Whole-mount in situ hybridization (WISH) was done according to the protocol published previously . Double-Proteins from worm footprints or worm tissue or pull-down experiments were reduced with 50 µL 10 mM DTT at 56 °C for 30 min and alkylated with 50 µL 55 mM iodoacetamide at room temperature for 20 min. Samples were digested either with trypsin, chymotrypsin, peptidase V8, lysine C, or lysine N at 37 °C overnight. The tryptic peptides were purified by ZipTip C18 pipette tips (Millipore) according to the manufacturer’s instructions before nano-LC-electrospray ionisation-MS analysis. Samples were analyzed using an UltiMate 3000 nano-HPLC system coupled to a Q Exactive mass spectrometer (both Thermo Scientific). Peptides were separated on a homemade fritless fused-silica microcapillary column (75 μm i.d. × 280 μm o.d. × 10 cm length) packed with 3-μm reversed-phase C18 material (Reprosil). Solvents for HPLC were 0.1% formic acid (solvent A) and 0.1% formic acid in 85% acetonitrile (solvent B).Data analysis was performed using Proteome Discoverer software (Thermo Scientific) with the search engine Squest against the translated MLRNA110815 and MLRNA131024 transcriptomes containing complete sequence of Mlig-ap1 and Mlig-ap2, while single transcripts belonging to the two proteins were manually deleted. Precursor and fragment mass tolerance was set to 10 ppm and 0.02 Da, respectively, and up to two missed cleavages were allowed. Carbamidomethylation of cysteine and oxidation of methionine were set as variable modifications. Peptide identifications were filtered at 1 or 5% false discovery rate. Data have been deposited to the ProteomeXchange Consortium  via the Luciferase dsRNA or without the presence of dsRNA. As shown in previous studies , and the protein was eluted with 5% formic acid. For control pull-down experiments, the PNA was preincubated with its inhibitory monosaccharide d-galactose (0.4 M) for 2 h at 4 °C. Identified peptides are listed in SI Appendix, Table S1.Lectin pull-down was done using Thermo Scientific Pierce streptavidin magnetic beads (88817). Briefly, protein from 1,000 tails was isolated and precleaned with 50 µL streptavidin magnetic beads. The precleaned protein was incubated with biotinylated PNA overnight at 4 °C. Then, the protein was incubated with streptavidin magnetic beads for 2 h at room temperature, magnetic beads were washed three times with Tris-buffered saline (TBS)  for 2 h at 4 °C.Anti–Mlig-ap1 and anti–Mlig-ap2 antibodies were raised in rabbits by GenScript. For Mlig-ap1, antibodies were produced against the following peptides: SRKPRRKNRKSRKP  and KNNKRRVRKARKNN . For anti–Mlig-ap2, antibodies against the following peptides were used: TSRKSTGRTTRQKK  and VNRETPKEPKKALS . A double labeling of adhesive gland cells with lectin PNA and polyclonal antibodies against Mlig-ap1 or Mlig-ap2 was done as described . Mlig-apFor footprint labeling, the above-mentioned antibodies and a third polyclonal antibody for Mlig-ap1 were used. It was generated according to the transcript sequence MLRNA110815_13121.1 against the peptide CRKSRKVNEEAWPRSP . This antibody did successfully stain Mlig-ap1 on the footprints but did not work in whole mounts.For footprint staining, approximately 20 worms were pipetted on a microscopy glass slide in a drop of ASW and left to adhere for 1 h at room temperature. Specimens were removed and footprints were fixed with 4% paraformaldehyde (PFA) for 30 min at room temperature and processed for antibody or lectin staining.2O. Footprints were stained with lead citrate for 30 s and rinsed with ddH2O. Images were taken with a Zeiss Libra 120 and iTEM software (Olympus).Chemical fixation and high-pressure freezing were performed as described . For TEMElectron spectroscopic imaging and electron energy loss spectroscopy were performed as described .Polysaccharides with vicinal hydroxyl groups were detected with periodic acid-thiocarbohydrazide-silverproteinate according to ref. Animals were allowed to adhere on a glass slide for about 15 min. Footprints were fixed chemically with 2.5% glutaraldehyde in 0.1 M cacodylate buffer containing 10% sucrose for 1 h. After several rinses with buffer, samples were postfixed with 1% osmium tetroxide in 0.05 M cacodylate buffer for 1 h. After washing, samples were dehydrated in methanol, critical point-dried (Pelco), and sputter-coated with 20-nm gold . Samples were examined with a Jeol JSM-7610F field emission scanning electron microscope at 5 to 15 kV.3, 30% H2O2, and 18.2 MΩ⋅cm Milli-Q water, for 10 min at 80 °C) before use. Si pieces were gold-coated in an electron-beam evaporation system with a base pressure of <2 × 10−8 mbar. A 20-Å Ti adhesion layer preceded a 2,000-Å Au layer, deposited at a rate of 1 and 5 Å/s, respectively. Thiols used to form SAMs, namely HS(CH2)15CH3  (Fluka), HS(CH2)15COOH  (Sigma-Aldrich), and HS(CH2)16NH2  (ProChimia), were used as received. The synthesis of HS(CH2)15CONH(CH2CH2O)nH, n = 1, 2, 4, 6, has been described previously  and contact angle measurements . Samples were packed under nitrogen, shipped by overnight courier from Linköping to Innsbruck, and kept in the dark at room temperature until used.SAMs were prepared on Si(100) wafers (Topsil) cut into 15-mm × 20-mm pieces which were TL1-cleaned  units in the EGx SAMs is in agreement with previously published data on similar series (Contact angle data for the SAMs are provided in r series , 76, 77.x >2 effectively resist the adsorption of proteins. The fouling resistance for these monolayers does not correlate directly with wettability or interfacial free energy, but the structural details of the surfaces are important. Both experiments (While all EGx surfaces are hydrophilic, there is a wealth of information indicating that there are important differences in the internal hydration of the EGx chains. For example, the differences in resistance to biofouling of EGx SAMs have been established in several experiments , 56, anderiments , 58 and eriments , 60 by Geriments , allowinFor adhesion assays, animals were incubated in the respective solutions and left for adaptation for 5 min. A single worm was pipetted on a microscopy slide in a small drop of medium and the attachments per min were counted. For surface tests, single worms were pipetted on the respective surface and the attachments per min were counted. Deposited footprints were processed for lectin or antibody staining. For releasing tests, single animals were put into the solution and the percentage of attached worms able to release within 30 s was evaluated. Movies of live animals were made using a Leica MZ16 F.Supplementary FileSupplementary FileSupplementary FileSupplementary FileSupplementary FileSupplementary FileSupplementary FileSupplementary FileSupplementary FileSupplementary FileSupplementary FileSupplementary FileSupplementary File


Autotrophic carbon fixation is a crucial process for sustaining life on Earth. To date, six pathways, the Calvin–Benson–Bassham cycle, the reductive tricarboxylic acid cycle, the 3-hydroxypropionate bi-cycle, the Wood–Ljungdahl pathway, the dicarboxylate/4-hydroxybutyrate cycle, and the 4-hydroxybutyrate cycle, have been described. Nano-organisms such as members of the Candidate Phyla Radiation (CPR) bacterial superphylum and the Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, Nanohalorchaeota (DPANN) archaeal superphylum could deeply impact carbon cycling and carbon fixation in ways that are still to be determined. CPR and DPANN are ubiquitous in the environment but understudied; their gene contents are not exhaustively described; and their metabolisms are not yet fully understood. Here, the completeness of each of the above pathways was quantified and tested for the presence of all key enzymes in nano-organisms from across the World Ocean. The novel marine ultrasmall prokaryotes were demonstrated to collectively harbor the genes required for carbon fixation, in particular the “energetically efficient” dicarboxylate/4-hydroxybutyrate pathway and the 4-hydroxybutyrate pathway. This contrasted with the known carbon metabolic pathways associated with CPR members in aquifers, where they are described as degraders ( The database consists of sequencing data from various sampling sites, depths, and fraction sizes, including an ultrasmall size fraction (<0.22 µm). About a hundred million sequences of predicted proteins have already been clustered by similarity using CD-HIT (The sequences used in this study were obtained from the TARA OCEAN metagenomic database (g CD-HIT . These cg CD-HIT .https://www.ebi.ac.uk/ena]) to identify potential environmental contaminants. This resulted in the removal of 142 sequences. Notably, autotrophic carbon fixation genes returned no matches with ≥80% sequence identity and a mutual alignment coverage of ≥80%, indicating that there was no positive evidence that these carbon fixation genes were carried by marine viruses.The clusters from PU, UO, and WUO were further curated by detecting viral proteins through similarity searches against the NCBI nr database (March 2017) using DIAMOND . This reMost annotated prokaryotes known to date, with the exception of nanosized members of the CPR and DPANN superphyla, were not expected to pass through a 0.22-µm filter. Therefore, the finding of proteins in the UO/WUO data sets that were highly similar to known regular-sized prokaryotes was likely due to contamination. For each sequence in our data set, the percentage of identity (%ID) to its best hit in nr was considered using DIAMOND. This was carried out in order to quantify how similar the environmental sequence was to a reference sequence. The step of taxonomic annotation allowed us to classify the environmental sequences from the UO and WUO clusters into two levels of increasing divergence from a reference, looking for potential organismal dark matter in the ultrasmall size fraction. Thus, the UO and WUO data sets were split into two nested categories: “dark matter” and “light dark matter.” Sequences whose best hit against nr showed a mutual coverage >80% and %ID <90% were assigned to “light dark matter” ; whereas sequences that showed %ID <70% %ID were assigned to “dark matter” . Furthermore, sequences taxonomically assigned to DPANN, unclassified bacteria, unclassified archaea, CPR, candidate or “root: unassigned” were assigned to both “light dark matter” and “dark matter,” because these taxa likely correspond to bona fide ultrasmall prokaryotes. The “dark matter” clusters provided an additional perspective, but “light dark matter” clusters were a priori not more (or less) contaminated than “dark matter” clusters.http://www.uniprot.org/mapping/) or the KEGG API service (March 2017).Using the KEGG database , a list E-value <1e-5, and mutual alignment coverage >70%  . The folage >70% . Using tA KEGG pathway describes a set of reactions (modules), which require a set of enzymes  online. Correlations between a pathway’s completeness and various assessments of the sequencing effort were computed with a Spearman correlation test, using the python3 function spearmanr from the SciPy library. Assessments of the sequencing effort for a given site were provided as the number of reads, high quality reads, predicted genes, and average read coverage per protein.P values for a 5% type I error.For each data set, the number of proteins assigned to a taxonomic group was compared with the PU data set. A pairwise Fisher exact test (using fisher_exact function from Scipy.stats Python3 library) was used to compare each taxonomic group with the remaining groups to identify significant enrichment or depletion compared with the PU data set. Because nine taxonomic groups were tested with six data sets, the corresponding Bonferroni correction was applied to the Reference sequences from KEGG and their environmental homologs were aligned with DIAMOND . A sequeE-value <1e-5  enzyme, fumarate hydratase, class II and the acrylyl-CoA reductase (NADPH)/3-hydroxypropionyl-CoA dehydratase/synthetase, suggesting a potential contribution to the HBC pathway  and numerous other compounds that are metabolized through acetyl-CoA and propionyl CoA  still included more than 50% of the enzymes involved in the HHC pathway within the set of sequences associated with the ultrasmall microbial “dark matter.” By contrast, little evidence of a complete WL pathway in the ultrasmall “light dark matter” and in the ultrasmall “dark matter” was found, although the WL pathway is thought to be the ancestral and the most energetically efficient autotrophic carbon fixation pathway.In sampling sites with high pathway completeness (≥60%), further investigations were carried out to identify key enzymes, that is, enzymes that were specific to a metabolic pathway and thought to have appeared once during evolution . The preIn the UO “light dark matter” data set, the DH pathway was still found in three sites but the CBB pathway was only complete in the pool data set; whereas in the UO “dark matter” data set, the CBB and DH pathways were both only complete in the pool data set.Ultrasmall prokaryotes have only recently been discovered, but what is known to date about their physiology highlights their uniqueness. Members of the CPR and DPANN superphyla from aquifers have recently been described as able to perform reactions related to carbon fixation, although they are usually described as degraders rather than carbon fixing . AlthougProchlorococcus and SAR11  the anaerobic and energetically efficient DH pathway was more than 50% complete at 33 sampling sites. Interestingly, this in contrast to the carbon fixation pathways associated with CPR and DPANN superphyla in aquifers , which svia metabolic hand-offs (Prochlorococcus or SAR11, currently the smallest described carbon fixing organism.Assuming microbial communities were sufficiently well sampled, the detection of partial metabolic pathways and associated key enzymes raises the question of the actual contribution of these genes to carbon fixation and cycling in the environment. These genes may play an effective role under two distinct conditions. First, the genomes hosting the partial pathways may also host alternative genes encoding for unknown enzymes that can perform the missing steps for carbon fixation. Second, alternative genes encoding unknown enzymes would perform the missing steps, which may be distributed across phylogenetically diverse community members and interacting and-offs . The conand-offs , but in Under both hypotheses, our study encourages single cell genome analyses and/or the binning of metagenomes into genomes of nanosized micro-organisms. This would allow further characterization of the precise mechanisms by which the organisms contribute to carbon fixation.Genome Biology and Evolution online.Supplement_Material_evz050Click here for additional data file.


Salvia miltiorrhiza, containing tanshinones and phenolic acids as its active compounds, has been widely used for the treatment of cardiovascular and cerebrovascular diseases. The biosynthetic analysis of secondary metabolites in S. miltiorrhiza has made great progress due to the successful genetic transformation system, simplified hairy roots system, and high-throughput sequencing. The cloned genes in S. miltiorrhiza had provided references for functional characterization of the post-modification steps involved in biosynthesis of tanshinones and phenolic acids, and further utilization of these steps in metabolic engineering. The strategies used in these studies could provide solid foundation for elucidation of biosynthetic pathways of diterpenoids and phenolic acids in other species. The present review systematically summarizes recent advances in biosynthetic pathway analysis of tanshinones and phenolic acids as well as synthetic biology and metabolic engineering applications of the rate-limiting genes involved in the secondary metabolism in S. miltiorrhiza.Secondary metabolites from plants play key roles in human medicine and chemical industries. Due to limited accumulation of secondary metabolites in plants and their important roles, characterization of key enzymes involved in biosynthetic pathway will enable metabolic engineering or synthetic biology to improve or produce the compounds in plants or microorganisms, which provides an alternative for production of these valuable compounds.  Plant secondary metabolites including terpenes, phenolic compounds, and nitrogen-containing compounds, which are served as signaling or defense molecules, are not only important to plant development and adaptation, but also have significant economic value as resources in human medicine and chemical industries. Many secondary metabolites from plants have been used in the clinical treatment of diseases, such as taxol in the treatment of refractory ovarian cancer and metastatic breast cancer , and ginHyoscyamus niger compared to the wild-type -phenylalanine to trace the metabolic origin of phenolic acids in S. miltiorrhiza. It was speculated that RA might be transformed into a phenoxyl radical by oxidation, and two phenoxyl radicals unite spontaneously to form SAB [S. miltiorrhiza, 4C-DHPL was considered as the main intermediate for RA biosynthesis, and DHPL was involved in this pathway as a principal intermediate. However, the pathway from RA to LAB remains to be elucidated  strategy for the rapid assembly of synthetic miltiradiene pathways in S. cerevisiae, using a fusion of the diterpene synthases SmCPS1 and SmKSL1 as well as the fusion of BTS1 (GGPPS) and ERG20 . This approach led to a significant improvement in the production of miltiradiene and a reduction of byproduct accumulation. The miltiradiene yield of the most prolific strain reached 365 mg/L in a 15-L bioreactor culture [tHMGR-upc2.1 and ERG20-BTS1-SaGGPS genes had a synergetic effect on the miltiradiene production in yeast strains, and 488 mg/L miltiradiene was produced in fed-batch fermentation [S. cerevisiae, Guo et al. engineered the yeast by incorporating modules expressing CYP76AH1 as well as a P450 reductase gene (SmCPR1) into this efficient pathway, leading to the heterologous production of ferruginol at 10.5 mg/L under flask shaking conditions without process optimization [The advances in recombinant DNA technology offered the opportunity of using synthetic biology to produce tanshinones and phenolic acid-related compounds in microorganisms. Zhou  culture . Furtherentation . Based omization . As the et al. [Escherichia coli through the overexpression of a six-enzyme chimeric bacterial and plant pathway. They compared three plant RAS orthologues from Coleus blumei (CbRAS), Lavandula angustifolia (LaRAS) and Melissa officinalis (MoRAS). The strains with different plant RAS genes produced different levels of RA and IA but in the same ratios, and the amount of RA and IA produced could also be increased by the optimization of another pathway. In S. miltiorrhiza, the analysis of phenolic acid biosynthesis could provide more candidate modules for pathway optimization. This work provided a microbial platform for the production of RA and IA that uses a modular biosynthetic approach to produce these compounds.The production of RA in microorganisms has also been realized. Bloch et al.  designedS. miltiorrhiza or its hairy roots provides an alternative method for accelerating the production of tanshinones and phenolic acids by overexpression the key enzymes or suppression the competition pathway. SmGGPPS, SmHMGR, and SmDXS were key enzymes involved in the biosynthesis of tanshinone precursors [S. miltiorrhiza, SmGGPPS1, SmHMGR1, and SmDXS2 were overexpressed in transgenic hairy root lines. It was revealed that the co-expression of SmHMGR1 and SmGGPPS1 resulted in the highest production of tanshinones (approximately 2.727 mg/g dw), which was approximately 4.74-fold higher than the production in the control (0.475 mg/g dw) [SmHMGR and SmDXR in S. miltiorrhiza hairy roots also significantly increased the production of tanshinones, especially with elicitor-mediated induction [The metabolic engineering of ecursors ,48,49,50mg/g dw) . The simnduction .S. miltiorrhiza hairy root cultures could be greatly increased by overexpression of SmC4H, SmTAT, and SmHPPR or by co-expression of SmTAT and SmHPPR. Co-expressing SmTAT1/SmHPPR1 produced the most abundant RA (906 mg/liter) and LAB (992 mg/L) in S. miltiorrhiza hairy root cultures, which were 4.3- and 3.2-fold more than in wild-type, respectively [et al. simultaneously expressed an ArabidopsisProduction of Anthocyanin Pigment 1 transcription factor (AtPAP1) and co-suppressed cinnamoyl-CoA reductase (SmCCR) and caffeic acid O-methyltransferase (SmCOMT), two endogenous key enzyme genes, in S. miltiorrhiza plants. The accumulation of SAB was up to three-fold higher in these plants than in the control. This was the first study to describe the production of valuable end products through combinational genetic manipulation in S. miltiorrhiza plants [SmHPPD), which was reported to compete with the biosynthesis of rosmarinic acid, was shown to inhibit the substrate competition from a bypassing pathway, thereby increasing the accumulation of phenolic acids [The production of RA and SAB in ectively . To enria plants . The supic acids .S. miltiorrhiza have been cloned either through a homology cloning strategy or by tissue-specific and induced-expression patterns. These genes have been functionally characterized in vitro or in vivo through enzymatic assays, RNAi, overexpression or isotopic labeling, which provide a basis for investigating the downstream pathways involved in tanshinone and phenolic acid biosynthesis. Firstly, co-expression analysis with the known functional genes could be employed as reference to narrow down the candidate genes obtained from various transcriptomes. In addition, comparative transcriptomes, such as those from different tissues, different development stages, and different induction times, as well as more efficient screening methods, should be applied to offer more information about the candidate genes involved in the biosynthetic pathway. Secondly, obtaining metabolic intermediates involved in biosynthetic pathways is extremely important for the analysis of downstream biosynthesis pathways, and given that the metabolic intermediates are always unstable and accumulated with low level, synthetic biology seems to be an increasingly important approach for analyzing biosynthetic pathways [in vitro enzymatic assays. In addition to synthetic biology, the chemical synthesis and exploration of intermediates from plants belonging to the same species are also effective approaches.Most genes involved in the biosynthesis of tanshinones and phenolic acids in pathways . The funS. miltiorrhiza have made significant progress. Tanshinones are widely extant in Salvia [Salvia will receive increasing attention. 13C tracer and precursor feeding experiments revealed that RA is likely to be the precursor of SAB [Coleus blumei (Lamiaceae) as well as in S. miltiorrhiza (Lamiaceae), and the enzymes involved in the biosynthesis of RA have also been elucidated in Melissa officinalis (Lamiaceae), Anchusa officinalis (Boraginaceae), and Lithospermum erythrorhizon (Boraginaceae) [S. miltiorrhiza have laid a foundation for the analysis of downstream biosynthetic processes, providing more modules for synthetic biology and references for the analysis of the biosynthetic pathways involved in producing phenolic acids and diterpenoids in both S. miltiorrhiza and other species.The studies on the biosynthetic pathway of tanshinones and phenolic acids in n Salvia , due to r of SAB . The bio


Here, we present ComPath, an ecosystem that supports curation of pathway mappings between databases and fosters the exploration of pathway knowledge through several novel visualizations. We have curated mappings between three of the major pathway databases and present a case study focusing on Parkinson’s disease that illustrates how ComPath can generate new biological insights by identifying pathway modules, clusters, and cross-talks with these mappings. The ComPath source code and resources are available at  Cataloging biological knowledge into pathways reduces complexity from all possible interacting molecular entities to a set of well-studied and validated functional relationships between molecular entities culminating in biological processes. Several efforts have generated databases of pathways with varying specificity and granularity that comprise signaling cascades, metabolic routes, and regulatory networks from precise signatures with no more than a couple of acting players to general pathways involving thousands of molecular players.Simplifying biology into pathways and representation as network models or mathematical models inevitably results in a loss of information such as spatiotemporal information or even entire biological entity types. The network abstraction facilitates pathway visualization and interpretation thanks to the harmony between biological networks and systems: nodes correspond to molecular entities and edges to types of interactions occurring between them . Although networks can comprise a broad range of molecular types , they are generally reduced to the most direct outcome of our genetic makeup - the genetic and protein levels - so that we can mechanistically understand their functionality. Thus, they are frequently viewed and simplified to “gene sets”, the collection of all genes/proteins that constitute the pathway, due to the major challenges of incorporating network topology and translating the variety of relationships into pathway analysis methods.5 community and crowdsourced efforts have recently gained traction.6 Further, the variability in curation team composition, database scope , and curation guidelines led to the adoption of different (and in many ways incompatible) schemata and formalisms such as Biological Pathway Exchange  and Systems Biology Markup Language . These incompatibilities motivated the integration and harmonization of resources into pathway meta-databases such as Pathway Commons9 and PathCards,10 which focus on integrating databases; iPath,11 which focuses on pathway visualization; and SIGNOR, which focuses on signaling pathways.12While dedicated research groups and commercial entities with experienced curators have lead a majority of the efforts to compile, delineate, and store biological knowledge into pathway databases,14 but most pathway databases had already been established by the time these ontologies were published. Therefore, consolidating pathway knowledge is a persisting issue and it is still required to map pathways from different resources together to improve database interoperability.Even after integrating multiple pathway databases into a pathway meta-database, it is difficult to assess the agreements, discrepancies, redundancy, and the complementarity of their contents because of the lack of availability of pathway mappings  in the original databases. These mappings are difficult to establish because of the arbitrary and overlapping nature of pathway boundaries as well as the absence of a common pathway nomenclature. Several controlled vocabularies have been generated as initial attempts to standardize pathway nomenclature,15 Though these approaches can systematically cluster pathways from multiple resources, there are some limitations to consider: first, the usual tradeoff between over/under-clustering,16 and second, pathway nomenclature and biological context are not considered by the clustering algorithm; it often leaves out equivalent pathways with low similarity and ignores the context of the pathway . Nevertheless, these limitations can be overcome by following clustering and prioritization methods with the manual curation required to interpret the abstract concepts that inherent to pathway definitions .Hierarchical clustering approaches have been presented as a way of grouping similar pathways based on their corresponding gene sets in order to propose pathway mappings.17 and tools18 have been successfully applied to interpret experimental data through the context of pathway databases,20 there has not yet been a systematic comparison between the contents of various pathway databases, an assessment of their overlaps and gaps, or an establishment of mappings. Previous studies have only focused on comparing a single or small set of well-established pathways across multiple resources.22 For example, a comparison focused on metabolic pathways revealed how a set of five databases only agreed in a minimum core of the biochemistry knowledge.23Though numerous algorithmsThese studies demonstrate the need to connect insights provided by each pathway database to foster a greater understanding of the underlying biology. Here, we present ComPath, a web application that integrates content from publicly accessible pathway databases, generates comparisons, enables exploration, and facilitates curation of inter-database mappings.We developed an interactive web application that enables users to explore, analyze, and curate pathway knowledge. Below, we present three case studies illustrating how it can be used for each of these purposes. The figures for each were generated by interactive, dynamic views in the ComPath web application based on three major public pathway databases: KEGG, Reactome, and WikiPathways Fig. .Fig. 1ThAnalysis of the overlaps between Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and WikiPathways revealed that there are ~3800 common human genes shared between the three databases Fig. . While a24 Figure While the previous views produced gene-centric summaries of the contents of pathway databases, ComPath also enables the exploration of pathway similarity landscape using Clustergrammer.js.27 with pathway-centric visualizations to identify modules, investigate overlaps, and cluster pathways. This case study demonstrates their use to investigate the roles of the pathways related to established genetic associations in the context of Parkinson's disease (PD).ComPath couples classic pathway enrichment analysis28 (the gene set will be referenced as PDgset) yielded over 300 pathways containing at least one of the panel's genes  by removing edges with a weight lower than 0.2  contained pathways related to the processes of endocytosis and vesicle transport, both of which are putatively disrupted in PD.31 M2 comprised pathways related to PTK6 signaling such as the Reactome pathway, PTK6 promotes HIF1A stabilization, whose high pathway enrichment significance , as well as its role in regulating another PDgset gene, ATP13A2,32 suggests that it may be linked to PD. ATP13A2 is directly responsible for Kufor-Rakeb syndrome,33 a rare juvenile form of PD, and participates in two other PD mechanisms: lysosomal iron storage and mitochondrial stress. Because pathways related to these two mechanisms  were also enriched by pathway enrichment analysis, we investigated the role of ATP13A2 in PD further.The pathway network view renders a pathway-to-pathway network in which nodes represent pathways and weighted edges represent their corresponding gene set similarities in a similar fashion to PathwayConnector.0.2 Fig. . The lar3 pathways . Because this activation leads to a reduction in mitochondrial stress and α-synuclein toxicity, two hallmarks of PD, ATP13A2 has been proposed as a therapeutic target.34 Ultimately, the exploration of the similarities and cross-talks between these three modules suggests further investigation of the candidate PD gene ATP13A2. Ultimately, this view complements pathway enrichment in the identification of pathway modules, exploration pathway cross-talks, and prioritization of genes for further study.ATP13A2 is activated by phosphatidylinositolbisphosphate, a particular phosphatidylinositol involved in M5, a module comprising the two Alzheimer's disease (AD) and two PD pathways from KEGG and WikiPathways. Subsequently, we used the ComPath pathway enrichment wizard to investigate in which pathways the common five genes identified  participate. The analysis revealed that they are predominantly involved in apoptosis, an important process in both AD and PD pathophysiology.36While the pathway network viewer provides an overview of the different modules and their cross-talks, it does not reveal information about their contained pathways' boundaries and intersections. Therefore, we implemented the pathway overlap view; an interactive Euler diagram that allows exploration of pathway demarcations Fig. . We empl2 . Additionally, the resulting dendrogram from clustering revealed hierarchical relationships between pathways , information that can be used to establish pathway mappings, as we show in the following case study.The third visualization renders the results of the hierarchical clustering approach described in Chen et al. in the form of a dendrogram, enabling deterministic pathway grouping based on gene set similarity. We used this view in the PDgset example to assign the pathways without module membership to the closest module  presented in the previous case studies as well as dedicated pathway pages where the content, descriptions, references, and the established mappings can be examined Fig. . FurtherAfter an exhaustive investigation of all possible mappings between pathways in KEGG, Reactome, and WikiPathways (see Methods), we identified 58 equivalencies between KEGG and Reactome, 64 between Reactome and WikiPathways, and 55 between KEGG and WikiPathways. Of these equivalent pathways, 21 are shared between the three resources Fig. . The highttps://github.com/ComPath/resources and https://compath.scai.fraunhofer.de/ so they can be revised, updated, and exploited by the research community hoping that this work serves as a first endeavor towards unifying pathway knowledge.The results of this curation effort are distributed at 37 Additionally, an embedded curation interface allow users to curate and establish mappings between pathways. Accordingly, we used ComPath to conduct extensive curation work to link the pathways from three major pathway databases in order to evaluate their similarities and differences. This mapping catalog serves as a first effort towards unifying and linking pathway information across databases that can later be adopted by the original databases or to create ontologies that store these mappings. Because databases regularly add new pathways and update gene identifiers, we plan to update ComPath biannually as well as curate mappings for these newly added pathways – current mappings do not have to be updated since the focus of the pathway does not change.The lack of a lingua franca in systems biology hampers the harmonization that would enable the exploration of the coverage, agreements, or discrepancies in the pathway knowledge. Harmonizing this information is an important step to better comprehend and model biology as well as improve the bioinformatics pipelines that utilize this knowledge to elucidate biological insights. As a first step towards closing this gap, we have implemented an environment capable of accommodating the pathway knowledge from multiple databases in order to facilitate its exploration and analysis through a web application. The flexibility of ComPath enables the incorporation of additional databases as well as dynamic update of its resources; the latter of which is often neglected, but can have a significant effect on derived analyses.The common genes between KEGG, Reactome, and WikiPathways covered the majority of pathways, indicating that their pathway knowledge is partially biased towards this shared gene set, even while there are still thousands of genes that have not yet been functionally annotated to pathways. Furthermore, our curation effort revealed that a surprisingly low number of pathways (21) were equivalent between KEGG, Reactome, and WikiPathways. On the other hand, the number of mapped pathways increased significantly when the hierarchical mappings were considered, revealing the inconsistent granularity employed to delineate pathway boundaries.10 Furthermore, recent studies revealed significant differences across a large sample of topology-based pathway analysis methods,38 and highlighted that gene sets alone might be sufficient to detect an enriched pathway under realistic circumstances.39 Hence, even if the abstraction of pathways as gene sets might not exploit all the existing pathway information, it is sufficient to drive an investigation of the pathway knowledge.Although the absence of topological pathway information in ComPath is an irrefutable limitation in this study, gene-centric approaches enable a reduction of complexity in pathway comparison as well as integration of resources which do not provide topology information.40 Furthermore, ComPath have been designed to accommodate multiple types of molecular entities participating in pathways ; thus, enabling to replicate the analyses presented with lipid or metabolite databases such as LIPEA41 or HMDB.42The established inter-database mappings allowed to link pathways from three major databases, opening the door towards a better integration of the pathway knowledge. In the future, these links can be used to complement and fill pathway knowledge as well as to conduct a precise evaluation of equivalent or related pathways by exploiting the available format converters such as the converter from Reactome to WikiPathways.In summary, we demonstrated that ComPath serves as an exploratory, analytic, and curation framework for pathway databases. Furthermore, we showed how the ComPath web application can complement enrichment approaches to elucidate and prioritize pathways and genes related to interesting biological phenomenon. Finally, we hope that the implementation of a curation ecosystem and the first mapping efforts conducted in this work pave the way towards unifying the pathway knowledge.At its core, ComPath is a framework for integrating pathway and gene set databases. We defined a set of guidelines for implementing wrappers around the processes of downloading data, transforming it into a common data model, and making queries. These guidelines are encoded in an abstract class with the Python programming language such that new plugins can be quickly implemented for new resources. Each implementation must have a mapping between genes and pathways as well as functions for exporting pathways as gene sets, performing pathway enrichment analysis, and performing reasoning/inference over pathway hierarchies.4 They can be used individually as a way of extracting, updating, and exploring the pathways contained within the database. Additionally, they can be used jointly in the ComPath web application where the pathways from multiple databases are integrated for their exploration, analysis, and curation.We implemented plugins for four major public pathway databases: KEGG, Reactome, WikiPathways, and MSigDB.43 in the public version of the ComPath web (https://compath.scai.fraunhofer.de/).The web application was implemented in the Python programming language using the Flask microframework and a suite of its extensions. The compatibility between Flask and the data models defined in all pathway plugins allows the integration and harmonization of the pathway knowledge in an extensible manner. To illustrate the flexibility of ComPath, we have included plugins for the Alzheimer’s disease and Parkinson’s disease gene sets associated with disease-specific mechanisms from NeuroMMSig24 and Cytoscape.js.44ComPath leverages a variety of state-of-the-art libraries for visualization and exploration of pathway knowledge. We chose Bootstrap for the design of the website since its responsive design retains full compatibility across all devices. Interactive visualizations are generated using several Javascript libraries, including D3.js, Clustergrammer.js,https://compath.scai.fraunhofer.de/apidocs. The API enables users to programmatically extract mapping information and perform queries using different genes or pathways identifiers.We implemented a RESTful API documented with an OpenAPI specification that can be accessed through the ComPath instance released at https://github.com/ComPath and https://github.com/Bio2BEL) under the MIT license. Both the plugins and the web application can be installed with PyPI (https://pypi.org), the main packaging system for Python. Furthermore, we have included a Dockerfile to enable reproducing the ComPath environment with Docker (https://www.docker.com/). Finally, documentation is included in each GitHub repository and it is also accessible at Read the Docs (https://readthedocs.org).The source code for ComPath and its plugins can be found on GitHub  have been used to assess the similarity between sets, the Szymkiewicz-Simpson coefficient (Eq. 1) is most appropriate for comparing sets widely varying in size. Similarly to previous studies, we have chosen this index to not only calculate pathway similarity but also reveal contained pathways  to indicate potential hierarchical relationships.equivalentTo. An undirected relationship denoting both pathways refer to the same biological process. The requirements for this relationship are: Scope: both pathways represent the same biological pathway information.Similarity: both pathways must share at minimum of one overlapping gene.Context: both pathways should take place in the same context .2.isPartOf. A directed relationship denoting the hierarchical relationship between the pathway 1 (child) and 2 (parent). The requirements are:Subset scope: the subject (pathway 1) is a subset of pathway 2 .Similarity: same as above.Context: same as above.Here, we describe a semi-automatic curation procedure we used in order to systematically generate equivalency and hierarchical mappings between the human pathways originating from KEGG, Reactome, and WikiPathways. Here, it is important to note that we have only focused on generating mappings for the pathways originating from each of the three resources, not their imported pathways from other databases . First, we define two types of mappings:1048Lexical similarity between each pair of pathways' names was calculated using the Levenshtein distance.Content similarity between each pair of pathways' genes was calculated using the previously described Szymkiewicz-Simpson coefficient.We generated all possible mappings between pathways in each database  and prioritized them based on the follow two independent metrics that have been proposed to calculate pathway similarity:https://github.com/ComPath/resources under the MIT License.After prioritization, our three curators from different areas of expertize  independently evaluated both similarities and the scope and context included in the pathway descriptions to assign the mapping types and to remove false positives. Furthermore, we investigated possible intra-database mappings within KEGG and WikiPathways since these resources do not yet contain hierarchical relationships. Finally, our curators combined the results and re-evaluated them to generate a consensus mapping file. It is available at Supplementary Text


Babesia orientalis, the causative agent of water buffalo babesiosis in China, is widespread in central and south China, resulting in a huge economic loss annually. Currently, there is no effective vaccine or drug against this disease. Babesia bovis and Plasmodium falciparum were reported to possess an apicoplast which contains the methylerythritol phosphate (MEP) pathway inhibitable by fosmidomycin, suggesting that the pathway could serve as a drug target for screening new drugs. However, it remains unknown in B. orientalis.The apicomplexan parasite Babesia microti and Babesia bovis. The genes were cloned, sequenced and analyzed. The open reading frames (ORFs) of the first two enzyme genes, 1-deoxy-D-xylulose 5-phosphate synthase (BoDXS) and 1-Deoxy-D-xylulose 5-phosphate reductoisomerase (BoDXR), were cloned into the pET-32a expression vector and expressed as a Trx-tag fusion protein. Rabbit anti-rBoDXS and rabbit anti-rBoDXR antibodies were generated. Western blot was performed to identify the native proteins of BoDXS and BoDXR in B. orientalis. Fosmidomycin and geranylgeraniol were used for inhibition assay and rescue assay, respectively, in the in vitro cultivation of B. orientalis.Primers were designed according to the seven MEP pathway genes of B. orientalis MEP pathway  were cloned and sequenced, with a full length of 2094, 1554, 1344, 1521, 654, 1932 and 1056 bp, respectively. BoDXS and BoDXR were expressed as Trx-tag fusion proteins, with a size of 95 and 67 kDa, respectively. Western blot identified a 77 kDa band for the native BoDXS and a 49 kDa band for the native BoDXR. The drug assay results showed that fosmidomycin could inhibit the growth of B. orientalis, and geranylgeraniol could reverse the effect of fosmidomycin.The seven enzyme genes of the Babesia orientalis has the isoprenoid biosynthesis pathway, which could be a potential drug target for controlling and curing babesiosis. Considering the high price and instability of fosmidomycin, further studies should focus on the screening of stable and cheap drugs. Plasmodium, Toxoplasma, Eimeria, Babesia and Theileria, contain a unique, relic, non-photosynthetic plastid-like organelle termed apicoplast [Plasmodium and Toxoplasma, including the methylerythritol phosphate (MEP) pathway for isoprenoid biosynthesis, FAS pathway and heme operate. In B. bovis and Babesia microti, the isoprenoid biosynthesis MEP pathway is the only metabolic pathway in the apicoplast [Many members of the Apicomplexa, including icoplast . The apiicoplast , 3. Isopicoplast .In nature, there are two distinct biosynthetic routes to produce IPP and DMAPP: methylerythritol phosphate (MEP) pathway and a modified mevalonate (MVA) pathway. The mevalonic acid (MVA) pathway was thought to be the only IPP and DMAPP biosynthetic pathway for decades . MammalsC-methyl-D-erythritol cytidylyltransferase (IspD), 4-diphosphocytidyl-2C-methyl-D-erythritol kinase (IspE), 2C-methyl-D-erythritol-2, 4-cyclodiphosphate synthase (IspF), 1-hydroxy-2-methyl-2-(E)-butenyl-4-diphosphate synthase (IspG) and 1-hydroxy-2-methyl-2-(E)-butenyl-4-diphosphate reductase (IspH) [C-methyl-D-erythritol 4-phosphate (MEP), which is a target for fosmidomycin [P. falciparum DXR, a rate-limiting enzyme of the MEP pathway, and the parasites will die for lack of isoprenoids (by blocking the conversion of DOXP to 2-C-methyl-D-erythritol 4-phosphate). Fosmidomycin is currently under Phase II clinical trials in combination with clindamycin and piperaquine against malaria [The MEP pathway is essential in eubacteria and protozoan but absent in humans and animals which could be the hosts of eubacteria and protozoan. The MEP pathway was discovered in the 1990s . In thise (IspH) . The secidomycin . Fosmido malaria –10.Babesia spp. are tick-borne intraerythrocytic protozoans and cause babesiosis globally. Babesia orientalis, a recently identified species epidemic in China, causes water buffalo babesiosis. The parasite is transovarially transmitted by Rhipicephalus haemaphysaloides which is the only reported vector of B. orientalis, and water buffalo is the only reported host. As a member of the family Babesiidae, B. orientalis has a similar life-cycle with other babesiid species, including a sexual stage within R. haemaphysaloides, followed by an asexual stage in water buffalo RBC. Babesiosis has become one of the most important water buffalo diseases in central and south China [B. orientalis. In this study, we proved that B. orientalis has the MEP pathway, and fosmidomycin can inhibit the growth of B. orientalis. The results demonstrate that the MEP pathway could serve as a potential target for screening anti-babesiosis drugs.th China . HoweverBabesia orientalis (Wuhan strain) was previously isolated from Wuhan city, Hubei Province, China, and preserved in liquid nitrogen in the State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, China.Babesia-free area. The buffaloes were tested by Giemsa staining and loop-mediated isothermal amplification (LAMP) to confirm that they were Babesia free/negative [B. orientalis positive blood (1% parasitemia). Blood was collected when the parasitemia of the infected buffaloes reached 3%.Three one-year-old water buffaloes were purchased from a negative . One watB. orientalis-infected blood using the QIAamp DNA Mini Kit  according to the manufacturer’s instructions. The DNA samples were used immediately or stored at -20 °C until use.Blood from the jugular vein of experimentally infected water buffaloes was collected in tubes containing EDTA . Genomic DNA was extracted from 200 μl of B. orientalis merozoites by using the TRIZOL reagent  and treated with RNase-free DNaseI . RNA concentration was measured by Nanodrop 2000. The cDNA was prepared from 1 μg of the total RNA using PrimeScriptTM RT reagent Kit with gDNA eraser  according to the manufacturer’s instructions.Total RNA was extracted from the purified B. orientalis MEP pathway were designed based on the gene sequences of B. microti and B. bovis . The recombinant protein was purified by affinity purification using a Ni-charged NTA column. Antisera against BoDXS were raised in rabbits.The open reading frame (ORF) of BoDXS was cloned into the pET-32a vector and expressed in B. orientalis, the lysates of erythrocytes prepared from B. orientalis and Babesia-free water buffaloes (the negative control) (0.5 mg per lane) were separated by 12% SDS-PAGE, transferred onto nitrocellulose membrane  and probed separately with rabbit serum raised against rBoDXS and pre-immune serum (1:100 dilution). The membranes were washed with PBST, and then incubated with the secondary antibody . The expression and identification of BoDXR were conducted as previously described for BoDXS.In order to identify the native DXS in B. orientalis in the water buffalo erythrocytes was cultured in M199 media  supplemented with 1% Albuman I (Gibco Life Technologies), 2% HB101 , 1% L-glutamine , 2% Antibiotic/Antimycotic 100×  and 20% healthy water buffalo serum with 10% hematocrit (HCT) at 37 °C in a microaerophilous stationary phase . The cultures were sub-cultured every three days when the parasitemia reached 2–3%.Briefly, B. orientalis cultures  were grown in 96-well flat-bottomed plates containing fosmidomycin in culture media. In the rescue experiments, the parasites were divided into five separate treatment groups . Diminazene aceturate was used as a positive control drug and ethanol was used as a blank control.Drug stock solutions of fosmidomycin  and diminazene aceturate  were prepared in sterile water. Geranylgeraniol  stocks were prepared in 100% ethanol. For the growth inhibition assay, During the 72 h incubation of the plates, three smears were prepared from each well and the parasitemias were determined every 24 h by microscopy. Thin blood smears were air-dried, fixed with methanol, and stained with Giemsa  according to the manufacturer’s instructions. The cultures were prepared in triplicate. The data were analyzed by GraphPad Prism 5 by one-way analysis of variance (ANOVA) followed by Turkey’s multiple comparison test. Error bars represent standard deviations.B. bovis and B. microti, the genomes encode all the seven components of the isoprenoid pathway, suggesting that the parasites have the MEP pathway [B. orientalis MEP pathway were amplified from both gDNA and cDNA and sequenced. The full lengths of DXS, DXR, IspD, IspE, IspF, IspG and IspH were 2094, 1554, 1344, 1521, 654, 1932 and 1056 bp, respectively , Plasmodium falciparum (AAD03739), Arabidopsis thaliana (NP_201085) and Escherichia coli (EGT67209)  from 1-deoxy-D-xylulose-5-phosphate (DOXP) in the presence of NADPH.BoDXS is intronless, encoding 667 aa with a predicted size of 77 kDa. BoDXR contains a 184 bp intron because the sequence obtained from cDNA is shorter than that of gDNA. It is the only intron gene in  XP_00161194, PlasC-methyl-D-erythritol 4-phosphate (MEP) by intramolecular rearrangement and reduction of DOXP [E. coli and purified by Ni-NTA affinity chromatography. The purified rBoDXS and rBoDXR revealed the two bands of 95 and 67 kDa on 10% SDS-PAGE, including an additional 18 kDa Trx-tag , the product of DXS, also participates in thiamine (vitamin B1) biosynthesis and/or pyridoxine (B6) synthesis , 17, indtag Fig. . AntibodC-methyl-D-erythritol 4-phosphate [Babesia is similar to Plasmodium in many aspects, and fosmidomycin was reported to be able to inhibit the intracellular growth of B. divergens at pharmacologically relevant concentrations [B. orientalis growth by fosmidomycin.The isoprenoid biosynthesis pathway generates isoprenoid precursors, and it is a promising chemotherapeutic target due to the difference between mammals and apicomplexan parasites in the seven enzymes of this pathway . To datehosphate . Fosmidohosphate , 10. Thetrations . HoweverB. orientalis was cultured and treated separately with 5 μM fosmidomycin, 5 μM fosmidomycin plus 5 μM geranylgeraniol, 5 μM geranylgeraniol plus 0.4 μM diminazene aceturate, 0.4 μM diminazene aceturate, and 0.1% ethanol. Diminazene aceturate was used as a positive drug control. Ethanol was used as a control because geranylgeraniol was soluble in ethanol (treated concentration 0.1%). The parasitemias were examined by Giemsa staining and light microscopy every 24 h. The results indicated that fosmidomycin was effective in inhibition of B. orientalis growth after 24 h  = 23.07, P = 0.0015) and 72 h treatment  = 73.21, P < 0.0001). However, there was no notable difference between fosmidomycin plus geranylgeraniol and control groups (both negative control and 0.1% ethanol)  Fig. . The effPlasmodium falciparum was reported to utilize the non-mevalonate isoprenoid biosynthesis in the apicoplast which is essential to the parasites [B. orientalis contains an apicoplast with a 34 kpb circular genome [B. orientalis indicated the presence of the substrate of this pathway, further suggesting that the MEP pathway is functional and required for the intraerythrocytic growth of B. orientalis merozoites, which is similar to that of B. bovis and P. falciparum [Plasmodium and Babesia which reside within erythrocytes [Theileria parva, but fosmidomycin showed no inhibitory effect even at a high concentration of 400 μM [arasites , 20, 21.r genome , but whelciparum , 21. Thehrocytes , 23. Thef 400 μM .B. orientalis. The native proteins of BoDXS and BoDXR were also identified, which demonstrated that the parasite contains the initial enzyme and the rate-limited enzyme of the MEP pathway. Additionally, the growth of B. orientalis could be inhibited by fosmidomycin while the effects of fosmidomycin could be reversed by medium supplemented with geranylgeraniol. These results indicated the existence of the isoprenoid biosynthesis pathway in B. orientalis, which could be a potential drug target for screening anti-babesiosis drugs. Further research should focus on the biological function of the MEP pathway in B. orientalis and the screening of new drugs using the E. coli model due to its identical isoprenoid biosynthesis pathway with apicomplexan parasites and easiness in manipulation.In the present study, we cloned and sequenced the seven enzyme genes of the MEP pathway in


Despite the progress in neuroblastoma therapies the mortality of high-risk patients is still high (40–50%) and the molecular basis of the disease remains poorly known. Recently, a mathematical model was used to demonstrate that the network regulating stress signaling by the c-Jun N-terminal kinase pathway played a crucial role in survival of patients with neuroblastoma irrespective of their MYCN amplification status. This demonstrates the enormous potential of computational models of biological modules for the discovery of underlying molecular mechanisms of diseases.Since signaling is known to be highly relevant in cancer, we have used a computational model of the whole cell signaling network to understand the molecular determinants of bad prognostic in neuroblastoma. Our model produced a comprehensive view of the molecular mechanisms of neuroblastoma tumorigenesis and progression.We have also shown how the activity of signaling circuits can be considered a reliable model-based prognostic biomarker.This article was reviewed by Tim Beissbarth, Wenzhong Xiao and Joanna Polanska. For the full reviews, please go to the Reviewers’ comments section.The online version of this article (10.1186/s13062-018-0219-4) contains supplementary material, which is available to authorized users. MYCN amplification status [Neuroblastoma is a tumor derived from primitive cells of the sympathetic nervous system that, despite advances in its treatment still has a poor survival for high-risk patients . Risk grn status . Althougn status . Moreoven status  providedn status . Moreoven status . Furthern status .MYCN amplification as well as to uncover the determinants of survival in neuroblastoma patients.Here, we have used generalized computational models covering all the signaling activity related with cancer hallmarks and other cancer-related signaling pathways. Such computational models use gene expression data to produce a realistic estimation of signaling circuit activity within pathways , which c2(1 + FPKM) were downloaded from the GEO database. In order to correct batch effect the COMBAT [A gene expression matrix with expression values quantified as loge COMBAT  method wMYCN amplification is a known biomarker of bad prognostic [MYCN amplification to those ones lacking this biomarker. Overall, our results document extensive differences at the level of signaling activity between patients with different MYCN amplification status. Specifically, patients with MYCN amplification seem to inhibit the JNK pathway, necessary for cell apoptosis, confirming in this way previous observations [CCL19, CCL21 and GADD45B, as depicted in Fig. MAPK8 within Ras, Fc epsilon RI and cAMP signaling pathways, seems to play an important role as mechanisms for the inactivation of the JNK pathway.Since ognostic  we were rvations . The mecMYCN amplification seems to be defective DNA repair. Again, the mechanism seems complex and mediated by many different pathways, which is not surprising, given that DNA repair must be a robust mechanism. A total of 5 circuits belonging to the pathways Jak-STAT, MAPK, ErbB, Wnt and Hippo signaling pathways present a highly significant deactivation in patients with MYCN amplification .For each circuit, patients irrespective of its BCL2L1). Apoptosis is massively inhibited through the inhibition of several circuits in the following pathways: Apoptosis  prognostic , also related to tumorigenesis [The patients with activation in circuit of the p53 signaling pathway ending in the  cancers , show a see Fig. . The proANGPT1 [FASLG via the corresponding circuit in the PI3K-Atk signaling pathway   and the ANGPT1  which apsee Fig. .BAX [− 5; see Fig. Interestingly, we found specific apoptosis induction of B cells mediated by the known apoptotic protein BAX  through MYCN amplifications. Only two circuits, Adipocytokine: PTPN11 and cAMP: AFDN are significantly associated to bad prognostic  gen involved in acute myeloid leukemias with t translocation, with a known role in cell adhesion [We also tried to find the molecular drivers of bad prognostic specific of patients with igration . The othadhesion .Fig. 4K-It has recently been demonstrated that model-based biomarker based on the activity of the JNK pathway robustly stratified neuroblastoma patients across different molecular backgrounds . ComputaThe use of models that quantify cell behavioral outcomes provides a unique opportunity to understand the molecular mechanisms of cancer development and progression , and ult2(1 + FPKM), was downloaded from the GEO database. Batch effect was corrected with COMBAT [The matrix GSE49711_SEQC_NB_TUC_G_log2.txt, with gene expression levels estimated by Cufflinks  and quanCircuit activities are modelled from gene expression values as described in . BrieflySn is the signal intensity for the current node n, vn is its normalized gene expression value, A is the set of activation signals (sa), arriving to the current node from activation edges, I is the set of inhibitory signals (si) arriving to the node from inhibition edges [Where on edges . In addion edges  or Unipron edges  definition edges .MYCN amplification status). In order to correct for multiple testing effects, the False Discovery Rate (FDR) method [p-values.Similarly to normalized gene expression values, circuit activities are measurements that do not make sense alone but rather in the context of a comparison. Thus, circuit activities can be used to compare conditions in the same way than gene expression values are used in a differential gene expression test. A Wilcoxon test is applied to assess the significance of the observed differences in circuit activities when two conditions are compared (e.g. ) method  is used http://hipathia.babelomics.org/.The model has been implemented in a web server freely available at: http://bioconductor.org/packages/devel/bioc/html/hipathia.html.Additionally, an R/Bioconductor script implementing the method is available at survdiff from the survival R package . This method provides a X2 statistic [p-value. Similarly to the case of two class comparison, multiple testing effects are corrected by FDR [Kaplan-Meier (K-M) curves  are usedtatistic  that is d by FDR .Tim Beissbarth.The manuscript describes an analysis on neuroblastoma data linking analysis of different pathways to molecular mechanisms in cancer and patient survival. Overall, this is an interesting and hypothesis driven modeling approach, that can better help to describe the functions of the cancer cell and thus leading to good survival models with a biological interpretation. However, I believe it also has some chances of over-fitting. I did not understand from the manuscript exactly how significance of their findings was assessed?Author’s response: The method recodes gene expression data into circuit (sub-pathway) activities. Then, differential activities between the conditions compared can be calculated. Significance is estimated in the same way differential gene expression significance is assessed. Here we use a Wilcoxon test. We have added a subsection to the methods section.Some external validation on an independent data-set would be of help.Author’s response: The original HiPathia paper  contains several independent data validations.Also comparison with other methods, either classical machine learning approaches or other pathway-structure oriented or classical gene set enrichment approaches might be interesting.Author’s response: Actually, we have recently published a benchmarking paper in which we demonstrate that Hipathia outperforms all competing methods . We have included a sentence at the end of the first paragraph in the Background section quoting this reference in the text.Overall, I believe this is an interesting study and modeling approach and does have some merit. Of course, to be clinically relevant more validation and further studies would be needed.Author’s response: We cannot agree more, but obtaining clinically relevant results is outside the scope of this manuscript, that deals with the analysis of the Neuroblastoma CAMDA dataset and focuses on the throwing light on the molecular mechanisms of neuroblastoma.If possible: - more detailed description of methods and statistical evaluation of significance - external validation on an independent data-set - comparison with other methods Critical points could also be discussed in the conclusion (to avoid overinterpretation or results).Author’s response: As mentioned above, we have added a new subsection to the Methods section to add more detail on the statistical validation of the values obtained. Comparison with other methods has been addressed in a separated paper and the result is that HiPathia outperforms the rest of pathway-based methods.Wenzhong XiaoIn this manuscript, Hidalgo etc. described their work using modeling to study cell signaling mechanisms of high-risk neuroblastoma and to predict disease outcomes. The paper is well written. Using Hipathia, an approach developed by the authors previously, they extracted comprehensively 1287 signaling circuits from 98 KEGG pathways and studied their activity in the neuroblastoma data. They first examined the impact of MYCN amplification on signaling pathways in neuroblastoma and it was comforting to see that the algorithm was able to identify well defined, reasonable signaling pathways affected by the MYCN amplification.In particular, the authors identified a set of circuits in patients with MYCN amplification that inhibit the JNK cascade. They then systematically studied each of the signaling circuits and successfully identified those which activities were significant associated with patient outcomes. The study demonstrated the feasibility of using modeling of signaling pathway activity in studying disease mechanism and developing prognostic biomarkers.Recommendations: 1. Page 3, line 54–55. Signal from RNA-seq data has a much wider distribution than that from array data, and usually a few genes have much higher expression than the rest. Can the authors clarify how the expression values were normalized between 0 and 1? In particular, according to eq. Author’s response: As we specified in methods we downloaded from the GEO database a matrix with gene expression levels normalized by FPKM and transformed as log2(1 + FPKM) values. FPKM is a well-known and accepted normalization method for RNA-seq that accounts for sequencing depth and gene length. Finally, we re-scale the values between 0 and 1 because of HiPathia method requirements. In principle we did not observed biases due to lowly expressed genes in the gene expression values are properly normalized. Moreover, as commented, a benchmarking carried out by us pointed to HiPathia as the best performer of all the pathway based analysis methods.The figures, for some reason, appeared to have very low resolution. For example, in Fig. Minor issues:2.Page 4, line 34, and other places in the text. Jack-STAT should be JAK-STAT.Author’s response: Fig. Author’s response: fixed.Joanna Polanska.The manuscript is devoted to study the activities of gene signaling pathways as triggers of neoplastic processes in neuroblastoma. The authors use their own computational algorithm, CCAA, previously published as , which eAuthor’s response: This is a very good question although including these results and commenting them is a bit away from the scope of this manuscript. Certainly, some circuits are correlated due to the dependence of some genes shared, which is an obvious correlation, but others not sharing genes are correlated as well, probably because they are under the same regulatory program. We have included a couple of sentences making reference to this comment at the end of the first paragraph of the Conclusions section.Author’s response: The idea was to discover these circuits remarkable related to survival. Therefore we had to clearly distinguish patients with high mortality rate from those with a low mortality rate and we thus focused on the extremes of the distribution. Splitting into two groups would reduce the detection sensitivity by including many patients with an intermediate survival in both groups.Author’s response: Probably, but there is no much information in TCGA regarding somatic mutations in neuroblastoma to reach solid conclussions.Author’s response: Yes, actually FDR is used although was not explicitly stated in the text because we referred to the original publication. However, the referee is right in noting this absence and we have explained the correction used (FDR) in a new subsection within the Methods section.Author’s response: We are pretty sure that a time-series circuit activity study would reveal very interesting results. The only coarse grain approach to study time progression of circuit activities in cancer we did is in the original paper describing the method  where we show how circuits corresponding to different cell functionalities changed across cancer stages. Some of them were initially activated in stage I and then remain with a similar activity, and we attributed them to cancer initiation functionalities, and some other increased its activity along cancer stages, and we guessed they were related to cancer progression cell functionalities.Additional file 1:. A) Different types of circuits can be defined within the pathways as subpathways that connect receptor proteins  to effector proteins (those at the end of the pathways). and ultimately to the functions behavioral outcomes triggered by the effector proteins. B) Elementary signaling circuits are defined as subpathways that connect a unique receptor to a unique effector protein; C) Effector circuits are defined as subpathways that connect a unique effector protein to all possible receptor protein that can start the transduction of signal; D) functional circuits are defined as subpathways that connect all the possible receptor proteins that can transduce signal to all the possible effector proteins that trigger a unique function. E) the concept of functional circuits is very convenient to define subsets of domain-specific functional circuits of relevance for the problem studied. For example, in cancer, the well-known cancer hallmarks can be identified among the GO terms of the functions triggered by the effector proteins. (JPG 250 kb)Schema of signaling circuit definitionAdditional file 2:Schema of the model of signaling circuit dynamics. A) The dynamics of the circuit is modeled taking the normalized gene expression values as proxies of protein activation status (the more expressed is a gene. The more likely the corresponding gene product will be active); B) given that both activations and repression activities can occur along the pathway, different scenarios are considered for the transmission of the signal: only activation, simultaneous activation and inhibition and only inhibition, which are coded in the formula; C) the application of the formula provided estimations of the different fluxes of signal across the circuit that finally arrive to the effector protein. In this way, a gene expression profile can be transformed in the corresponding signaling circuit activity profile . (JPG 149 kb)


Recent identification of 10 germline variants predisposing to monoclonal gammopathy of undetermined significance (MGUS) explicates genetic dependency of this asymptomatic precursor condition with multiple myeloma (MM). Yet much of genetic burden as well as functional links remain unexplained. We propose a workflow to expand the search for susceptibility loci with genome-wide interaction and for subsequent identification of genetic clusters and pathways.Polygenic interaction analysis on 243 cases/1285 controls identified 14 paired risk loci belonging to unique chromosomal bands which were then replicated in two independent sets . Further investigation on gene-set enrichment, regulatory pathway and genetic network was carried out with stand-alone in silico tools separately for both interaction and genome-wide association study-detected risk loci.PREX1 (20q13.13), a reported locus predisposing to MM was confirmed to have contribution to excess MGUS risk in interaction with SETBP1, a well-established candidate predisposing to myeloid malignancies. Pathway enrichment showed B cell receptor signaling pathway (P < 5.3 × 10− 3) downstream to allograft rejection pathway (P < 5.6 × 10− 4) and autoimmune thyroid disease pathway (P < 9.3 × 10− 4) as well as epidermal growth factor receptor regulation pathway (P < 2.4 × 10− 2) to be differentially regulated. Oncogene ALK and CDH2 were also identified to be moderately interacting with rs10251201 and rs16966921, two previously reported risk loci for MGUS.Intronic-We described novel pathways and variants potentially causal for MGUS. The methodology thus proposed to facilitate our search streamlines risk locus-based interaction, genetic network and pathway enrichment analyses.The online version of this article (10.1186/s10020-018-0031-8) contains supplementary material, which is available to authorized users. Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant phase of multiple myeloma (MM) and the most common plasma cell dyscrasia present in as high as 3.2% of general population below 50 years of age and up to 5.3% for population aged 70 years or older  were males with a mean age at diagnosis of 62 years, SD ± 11 years. The Ig isotype distribution was 72% IgG, 12% IgA, and 16% other Ig isotypes  genotyped on the same array. Application of similar quality control protocol rendered 195,490 autosomal SNPs present in 236 cases and 2484 controls of Essen GWAS set.We excluded SNPs with less than 1% minor allele frequency, and also if the call rate was less than 99% in cases and controls. Genotype distribution in controls was tested for Hardy-Weinberg equilibrium with a χ2 test with 1 degree of freedom or Fisher’s exact test and SNPs with 11 interactions. However, linkage disequilibrium (LD) among the SNPs, if not taken into account in argument space, possibly renders a large portion of tests redundant which destabilizes the test statistic. To avoid this deflation of test power, we employed Wellek-Ziegler statistic which promises high variance stability and unbiased estimate on the condition of Hardy-Weinberg equilibrium conformity  between alleles of two loci irrespective of phenotypic categorization. Assuming the general population (control group) is devoid of any correlation between the specific loci, the case-only approach ensures evidence of gene-gene functional pair interactions with higher power in detection due to reduced number of multiple testing. As the risk loci are tested against each other rather than a reference set, allelic co-occurrence indicates bi-allelic interaction jointly predisposing phenotype changes  , REACTOME and BioCarta libraries were used for pathway enrichment.Due to LD, causal regulatory elements often remain unidentified in genome-wide association studies. To gain biological insight, pathway analysis via gene-set enrichment is traditionally carried out to integrate signals from different sentinel variants and linked SNPs. We applied three tools designed for biological interpretation of GWAS: Pathway Scoring Algorithm (PASCAL), Data-driven Expression Prioritized Integration for Complex Traits (DEPICT) and Meta-Analysis Gene Set Enrichment of Variant Associations (MAGENTA). PASCAL is a pathway analysis tool developed for association summary statistics for variants annotated to genes. PASCAL uses maximum of chi-squares (MOCS) or sum of chi-squares (SOCS) statistics with null distribution as Gamma with varying degrees of freedom  at 1%  from the discovery set had a Wellek-Zeigler (W-Z) P = 4.19 × 10−13 and a simple logistic regression P = 8.67 × 10−11  which restricted the number of tests performed to an approximate 1.25 × 107 pairs. Subsequently, 693 unique interaction pairs were identified at 5 × 10−5significance level where none of the observations reached genome-wide threshold of approximate 8 × 10−10 calculated taking Bonferroni correction into account on 99% confidence level. The top interaction was found to be between rs10099120 and rs3738270 with P = 9.05 × 10−8 and we note, rs10099120 is located in the intronic region of RALYL and rs3738270 corresponds to a missense mutation on IGFN1  showed a case-only P = 3.35 × 10−24 against W-Z case-control P = 1.5 × 10−12. At 5 × 10−10 level we detected 352 variant pairs replicated in the discovery set with varying levels of significance . Among the 23 replications, 14 were unique regions and there were 5 regions with multiple unique interactions. Interestingly, SETBP1 and PREX1 interaction at 18q12 and 20q13 were represented by 6 SNP-SNP pairwise overlaps with LD coefficient of r2 < 0.2 between SNPs belonging to corresponding regions. The locus at 20q13 has already been identified as a predisposing locus for MM and as an expression and methylation quantitative trait locus at PREX1 without affecting an active promoter site  with rs8092870 , W-Z P = 1.71 × 10−7. Although both the latter two SNPs are located at 18q12, they are not in LD ( r2 < 0.2).Next, we evaluated W-Z interactions by CASSI in the case-control replication set consisting 8.2 × 10P = 7.09 × 10−5) and 3 gene nodes downstream to KEGG B cell receptor signaling pathway (P = 5.32 × 10−3) were found to be the two most significant pathways.A partnership dependence structure of functional network was constructed with the risk variants from the final overlapping set subject to identifiable annotation from the interaction analyses. Twenty-six such reconstituted genes were used as nodes which together with first order interacting genes created scaffolding for further enrichment analysis Fig. . Thirty-P < 0.025   and KEGG autoimmune thyroid disease pathway (combined P = 5.41 × 10−6), both related to B cell receptor signaling pathway, were the two most significant ones. Thus we determine that the B-cell receptor signaling pathway and EGFR regulatory pathway are present in both the interaction and genome-wide association study-oriented pathway analyses with statistical significance.Similar to genome wide-association and interaction studies, pathway enrichment for MGUS is still unexplored in literature due to obvious limitations regarding caveats in identification and inclusion of adequate MGUS cases. We identified 65 enriched pathways at 95% confidence (19 at 99%) employing PASCAL . Involvement of HER4 in cancer has yet not been comprehensively addressed, although it has been shown to be overexpressed in colorectal cancer and postulated to promote carcinogenesis in general  and autoimmune thyroid disease (hsa05320) pathways with highest combined power from all three GWAS enrichment algorithms. Conspicuously B cell receptor signaling which is enriched in our genetic network is also downstream to both of the pathways. This pathway is shown to be dependent on mitogen-activated protein kinase signaling (MAPK), phosphatidylinositol-3 kinase and protein kinase B signaling (PI3K-Akt), nuclear factor κB signaling (NF-κB) and calcium signaling pathways. It is also dependent on adhesion molecule induced mechanisms that mediate immune tolerance in T cell receptor signaling cascade. Detection of ErbB signaling (hsa04012) in genetic network enrichment is also supported by detection of EGFR downregulation pathway from our pathway analysis. We identified ErbB4 (HER4) to be a high-risk locus interacting with 15q22 and 9p23. ErbB4 is one of the four epidermal growth factor receptor (EGFR) family members with tyrosine kinase activity. In both cancerous and non-cancerous cells, EGFR plays a crucial role in controlling key cellular pathways influencing cell proliferation, differentiation and development through MAPK and PI3K/Akt pathways and overexpression of which is associated to multiple cancer types . Notably ALK amplification, mutations and especially chromosomal rearrangements have been found in several cancers  pathway, a crucial adhesion mechanism not only in normal hemostasis but also in pathophysiological processes such as inflammation, immune-mediated host defense and cancer metastasis. Integrin-αIIbβ3 plays a key role in platelet adhesion and aggregation Top interactions from W-Z discovery set interaction test compared with simple logistic linear interaction test (brute force epistasis). Description: SNP1 and SNP2 are the two SNP candidates of a pair from the discovery population belonging to chromosomes denote by Chr1 and Chr2; gene1 and gene2 are the corresponding genes annotated to SNP1 and SNP2, respectively. W-Z Additional file 2:P value is Wellek Ziegler case-only test p-value; BP is base pair. (DOCX 21 kb)Top interactions from W-Z case-only test in confirmation set. Description: SNP1 and SNP2 are the two corresponding SNP candidates of a pair from the case-only population belonging to chromosomes denote by Chr1 and Chr2; gene1 and gene2 are the corresponding genes annotated to SNP1 and SNP2, respectively. W-Z Additional file 3:P value is Wellek Ziegler case-control test p-value; BP is base pair. (DOCX 22 kb)Top interactions from W-Z interaction test on the replication set. Description: SNP1 and SNP2 are the two SNP candidates of a pair from the replication set population belonging to chromosomes denote by Chr1 and Chr2; gene1 and gene2 are the corresponding genes annotated to SNP1 and SNP2, respectively. W-Z Additional file 4:P value is Wellek Ziegler case-control test p-value from CASSI and INTERSNP P value is full log-linear test p-value from INTERSNP; BP is base pair. IN: INTERSNP; CAS: CASSI. (DOCX 22 kb)Overlapped interactions from INTERSNP and CASSI W-Z interaction tests on discovery set. Description: SNP1 and SNP2 are the two SNP candidates of a pair from the discovery set population belonging to chromosomes denote by Chr1 and Chr2; gene1 and gene2 are the corresponding genes annotated to SNP1(s) and SNP2(s), respectively. W-Z Additional file 5:P values are corrected for multiple testing. A protein-protein enrichment index is reported with analysis depicting level of confidence in the detected enriched processes which is reported to be 0.0039 (significant at 5% level). (DOCX 21 kb)Gene set enrichment analysis in genetic network with STRING. Description: Based on the indexing nodes and the additional predicted first order interacting m=nodes, STRING performs enrichment analysis on several molecular, biological, cellular process related pathway analysis with Gene Onltology (GO) and KEGG database. All tests are performed with guilt by association assumption and Additional file 6:PASCAL gene set enrichment analysis results at 1% level of significance. (DOCX 20 kb)Additional file 7:MAGENTA gene set enrichment analysis results at 1% level of significance. (DOCX 20 kb)Additional file 8:All detected pathways mutually discovered in both MAGENTA and PASCAL at a 5% level of combined significance. (DOCX 21 kb)Additional file 9:DEPICT gene set enrichment analysis results at Bonferroni corrected genome wide significance level. (DOCX 18 kb)Additional file 10:Summary of Illumina bead chips used for genotyping different batches of cases and controls. (DOCX 19 kb)Additional file 11:Number of overlaps in number of SNPs prior quality control between different chips used in genotyping. Chip numbers are defined in Additional file