Centipedes are among the most ancient groups of venomous predatory arthropods. Extant species belong to five orders, but our understanding of the composition and evolution of centipede venoms is based almost exclusively on one order, Scolopendromorpha. To gain a broader and less biased understanding we performed a comparative proteotranscriptomic analysis of centipede venoms from all five orders, including the first venom profiles for the orders Lithobiomorpha, Craterostigmomorpha, and Geophilomorpha. Our results reveal an astonishing structural diversity of venom components, with 93 phylogenetically distinct protein and peptide families. Proteomically-annotated gene trees of these putative toxin families show that centipede venom composition is highly dynamic across macroevolutionary timescales, with numerous gene duplications as well as functional recruitments and losses of toxin gene families. Strikingly, not a single family is found in the venoms of representatives of all five orders, with 67 families being unique for single orders. Ancestral state reconstructions reveal that centipede venom originated as a simple cocktail comprising just four toxin families, with very little compositional evolution happening during the approximately 50 My before the living orders had diverged. Venom complexity then increased in parallel within the orders, with scolopendromorphs evolving particularly complex venoms. Our results show that even venoms composed of toxins evolving under the strong constraint of negative selection can have striking evolutionary plasticity on the compositional level. We show that the functional recruitments and losses of toxin families that shape centipede venom arsenals are not concentrated early in their evolutionary history, but happen frequently throughout. Venom is one of nature’s most frequently evolved adaptations. A conservative estimate suggests it has evolved more than 80 times in the animal kingdom to play important roles in predation, defense, blood feeding, and other functions . Venoms This study focuses on the venoms of centipedes (Myriapoda: Chilopoda), an ancient group of predatory arthropods with more than 3,100 described species. Centipedes are among the oldest known terrestrial venomous lineages, with a fossil record going back at least 420 My. A diagnostic trait of centipedes is the modification of their first walking appendages into venom-delivering claw-like structures called forcipules. Because all known extant centipede species have a forcipular venom system, and forcipules are known from the oldest known centipede fossils, venom is assumed to have evolved once in the stem lineage of centipedes. The living species belong to five lineages that are classified as orders : ScutigeScolopendra   proteins, and cysteine-rich peptides , phosphodiesterase (S. morsitans), calycin/lipocalin (C. tasmanianus), IgE Epididymal secretory protein-like , and Pesticidal Crystal Protein Domain-containing Protein-like proteins . The remaining nine toxin families represent novel proteins and peptides, including two protein families with no similarity to any characterized protein or domain , and seven new venom peptide families with no recognizable similarity to any described peptide or peptide fold. Of these new peptide families, three were found only in the venom of L. forficatus , one was found in the venoms of C. tasmanianus and Strigamia maritima , and two were found only in the venom of Stm. maritima .To identify and classify venom components with putative toxic function, and to minimize toxin annotation error rates , we usedMapping the sequences identified in the venom gland transcriptomes A and venVariation in sequencing depth can also complicate the comparison of transcriptomic venom profiles. The six transcriptomes generated on the Illumina NextSeq platform contain more contigs than those generated with Roche 454 technology. This impact of sequencing method is revealed when we perform a phylogenetic analysis of the distribution of toxin families, using a data set that scored the absence/presence of each family in the transcriptomes  online. Scolopendra species have the most complex venoms, with 47 (S. morsitans) and 48 (S. subspinipes) toxin families. The scutigeromorphs and the geophilomorph have the simplest venoms, with 8 and 12 toxin families in the venoms of the scutigeromorphs Scutigera coleoptrata and T. longicornis, respectively, and 12 toxin families in the venom of the geophilomorph Stm. maritima. The other species have venoms of intermediate complexity, with the number of toxin families ranging from 17 in the craterostigmomorph C. tasmanianus to 28 in the scolopendromorph Ethmostigmus rubripes. Furthermore, the venoms of most species contain between three and eight unique toxin families, except the scutigeromorph Sc. coleoptrata and the scolopendromorph Cormocephalus westwoodi, with there being no toxin families unique for these species. When judged by the number of unique relative to the total number of toxin families found in their venoms, the craterostigmomorph and the lithobiomorph venoms emerge as the most distinctive, with respectively 47% and 35% of their putative toxin families not being found in any other species . All gene alignments can be found in An example of a family with a complex evolutionary history is the β-PFTx family, which was recruited as one of the first venom components in the common centipede ancestor. Gene tree/species tree reconciliation suggests that the evolution of this family is governed by gene family expansions as well as functional losses at different times during the evolutionary history of centipedes . Our datSuch taxonomically restricted evolution is common for centipede venom toxin families. This pattern is evidenced by the number of order-specific toxin families, but it is also evident among toxin families that are shared between orders. In these taxonomically more widespread toxin families, the main radiations appear to have occurred not within orthologous toxin clades, but ancient paralogous toxin clades. Examples of this include β-PFTx, where about half of the main toxin clades show evidence of centipede lineage-specific diversification , and M12In addition to lineage-specific toxin diversification and multiple independent recruitments of single protein and peptide families, phylogenetic analyses revealed several cases of paralogous toxin clades densely interspersed by closely related but likely nontoxin centipede homologs, including nonvenom gland (trunk) sequences. This pattern was found in eight toxin families, namely the M12A proteases , GH18 hyThe processes that shape the genetic diversity of toxin families set the parameters for what is possible during venom evolution, but our data show that the evolution of venom composition has its own distinctive dynamics. We therefore reconstructed the macroevolutionary history of functional recruitments and losses of toxin families from centipede venom proteomes, using parsimony-based character state optimizations informed by our phylogenetic analyses of toxin gene families  and 6 , a putative pore-forming toxin (β-PFTx), and a cysteine-rich protein (CAP1) . This fiUndheim, Jones, et al. 2014Our ancestral reconstructions suggest that centipede venoms remained simple cocktails for much of the early evolutionary history of the group, with relatively little compositional evolution occurring along the lineages leading to Pleurostigmophora, Phylactometria, and Epimorpha. It is possible that more compositional evolution occurred in these basal parts of the centipede tree, but that this has become obscured by subsequent evolution. This is unlikely, however, because these internodes also have short branch lengths in phylogenomic trees and chronograms of centipede relationships. That indicates that these internodes bracket relatively small amounts of molecular evolution and evolutionary time compared with the order-level lineages diverging from these internodes , 2016. Mdomain of unknown function), uncharacterized protein family 4 (a protein family with no similarity to characterized proteins or domains), Scutigerotoxin 2 (SCTX02), and SLPTX01. The first three of these are unique for scutigeromorphs, whereas SLPTX01 has been convergently recruited into scolopendromorph venoms. Interestingly, the venom of Sc. coleoptrata is identical to that reconstructed for the scutigeromorph ancestor, whereas T. longicornis has recruited an additional five protein families and lost GH18 from both its venom and venom gland transcriptome. The pleurostigmophoran ancestor recruited just one additional protein family to the ancestral centipede venom, the peptide family SLPTX22. A modest increase in venom complexity subsequently evolved along the stem lineage leading to Phylactometria, with the recruitment of two protein families (CHLTX01 and SLPTX04). Three more protein families  were recruited into the ancestral epimorphan venom, but its complexity remained the same as that of the phylactometrian ancestor (seven protein families) because of the loss of three protein families along the epimorphan stem lineage . These increases in venom complexity along the stem lineages of Pleurostigmophora, Phylactometria, and Epimorpha are with the exception of a single protein family (cystatin) entirely due to the recruitment of peptides, resulting in an increase in the proportion of venom peptide families from none in the ancestral centipede venom, to 20% in the ancestral pleurostigmophoran venom, 43% in the ancestral phylactometrian venom, and 71% in the ancestral epimorphan venom  with the recruitment of 4 protein families and the loss of 1, before another massive increase in venom complexity evolved along the base of the genus Scolopendra, with the recruitment of 17 and the loss of 2 protein families. Although the reason for this sudden increase in toxin diversity is unclear, it is tempting to speculate that it may be related to a combination of increases in venom gland complexity and body size, which enabled an ecological shift from largely arthropod-restricted prey to an opportunistic and more diverse diet that included larger vertebrate prey. An increase in the diversity of venom toxins has been correlated with a change to a more diverse diet in cone snails and spiders , L. forficatus (Lithobiomorpha), C. tasmanianus (Craterostigmomorpha), and Stm. maritima (Geophilomorpha). We also resequenced S. morsitans (Scolopendromorpha), previously analyzed by T. longicornis (NCBI transcriptome shotgun assembly [TSA] accession GASR) and the scolopendromorphs E. rubripes (TSA accession GASI), Co. westwoodi (TSA accession GASL), and S. morsitans (TSA accession GASH). The data for these species were analyzed using the same proteotranscriptomic and phylogenetic approach as used here, but their transcriptomes were sequenced with Roche 454 technology and assembled using MIRA (S. subspinipes (TSA accession GGDW), which was analyzed according to the same protocols used here and sequenced on an Illumina NextSeq platform  approach: ing MIRA . We alsoplatform . The proL. forficatus specimens were collected at Tooting Bec Common (seven specimens) and near Hither Green (one specimen) in London, United Kingdom, and forcipules from these specimens were dissected and pooled for transcriptomic profiling. Specimens for proteomic analyses were collected in Greifswald, Germany. Specimens of Stm. maritima for transcriptomic and proteomic analyses were collected near Brora, Scotland. The forcipules of 80 males and 57 females were dissected and pooled for each sex to create 2 transcriptomic profiles. These profiles were combined for all downstream analyses. Specimens of Sc. coleoptrata for transcriptomic and proteomic analyses were collected in Ibiza, Spain. The forcipules of 20 specimens were dissected and pooled for transcriptomic profiling. Specimens of C. tasmanianus for transcriptomic and proteomic analyses were collected near Hellyer Gorge in Tasmania, Australia, and forcipules from five adults dissected and pooled for transcriptomic profiling. The regenerating venom glands from a single female S. morsitans collected in Glenmorgan, Queensland, Australia were resequenced as well.Eight L. forficatus, C. tasmanianus, Stm. maritima, and S. morsitans, we sequenced the transcriptomes of forcipules or dissected venom glands (S. morsitans) 2 days after depleting venom by electrostimulation. The forcipules of Sc. coleoptrata were dissected without depleting the venom glands beforehand because the animals recovered very poorly from electrostimulation. Total RNA was extracted from all samples using standard TRIzol protocol (ThermoFisher). For C. tasmanianus and S. morsitans, samples were submitted to the University of Queensland Institute for Molecular Bioscience Sequencing Facility for library preparation and sequencing. Paired-end libraries with 180 bp insert size were constructed using the Illumina TruSeq-3 Stranded mRNA kit and sequenced on an Illumina NextSeq using a 300 cycle (2 × 150bp) Mid Output Run. The samples for Stm. maritima, L. forficatus, and Sc. coleoptrata were submitted to the Natural Environment Research Council Center for Genomic Research at the University of Liverpool for library preparation and sequencing. The libraries were paired-end sequenced on an Illumina HiSeq2000 platform, with 100 bp insert size. The resulting reads were trimmed with Trimmomatic 0.35 .For tic 0.35  with a ph FastQC , then prh FastQC  to removh FastQC  applyingTo identify proteins and peptides present in the venom, venom obtained by electrostimulation was analyzed by a bottom-up approach. For each sample, 5 µg crude venom was dried by vacuum-centrifugation and redissolved in 4 M urea 10% ACN 100 mM ammonium bicarbonate, pH 8. Cystines were then reduced by incubating with 5 mM dithiothreitol at 70 °C for 5 min and alkylated with 10 mM iodoacetamide at 37 °C for 90 min. The reduced and alkylated samples were then digested by incubating with 30 µg/µl trypsin overnight at 37 °C in 2 M urea 10% ACN 100 mM ammonium bicarbonate, pH 8, at a final substrate to enzyme ratio of approximately 100:1. The resulting tryptic peptides were desalted using a C18 ZipTip (ThermoFisher), dried using vacuum centrifugation, dissolved in 0.5% formic acid (FA), and 2 µg analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS) on an AB Sciex 5600 TripleTOF equipped with a Turbo-V source heated to 550 °C. The dissolved samples were fractionated on a Shimadzu  Nexera UHPLC with an Agilent Zorbax stable-bond C18 column (Agilent) , using a flow rate of 180 µl/min and a gradient of 1–40% solvent B  in 0.1% FA over 60 min. MS1 spectra were acquired at 300–1800 m/z with an accumulation time of 250 ms, and selecting the 20 most intense ions for MS2. Precursor ions with a charge of +2 to +5 and an intensity of at least 120 counts/s were selected, with a unit mass precursor ion inclusion window of ±0.7 Da, and isotopes within ±2 Da were excluded. MS2 scans were acquired at 80–1400 m/z, with an accumulation time of 100 ms, and optimized for high resolution.The resulting MS/MS spectra were then searched against the respective species’ assembled transcriptomes translated to all 6 possible open reading frames longer than 40 amino acids using the Galaxy tool “Get open reading frames (ORFs) or coding sequences (CDSs)”  using Prhttps://data.nhm.ac.uk/dataset/evolution-of-centipede-venoms; last accessed July 23, 2019). All mass spectrometry and ProteinPilot data were submitted to the ProteomeXchange Consortium via the PRIDE (All raw sequence data were submitted to the Sequence Read Archive (SRA) of the National Center for Biotechnology Information (NCBI) under BioProject ID PRJNA540703, with BioSample accessions SAMN11553657, SAMN11553658, SAMN11553659, SAMN11553660, SAMN11553661, and SAMN11553662. Transcriptome assemblies are available via the Natural History Museum’s Data Portal  of all nonredundant contigs  belonging to each of the 93 identified putative toxin gene families against the full UniProtKB protein database  , then aligned all significant hits using the local paired iterative alignment method (L-INS-i) in MAFFT v7.304b  . We also0, 2016)  online.  v7.304b , and use v7.304b  online a v7.304b  online.  v7.304b  and used v7.304b  for reco v7.304b . Finally v7.304b  to map tMolecular Biology and Evolution online.msz181_Supplementary_DataClick here for additional data file.


ST outlier tests. Candidate genes that may underlie differences in adaptation to specific environments and productive systems and phenotypic traits were detected in potentially selected genomic regions.Genetic characterization of local breeds is essential to preserve their genomic variability, to advance conservation policies and to contribute to their promotion and sustainability. Genomic diversity of twenty European local pig breeds and a small sample of Spanish wild pigs was assessed using high density SNP chips. A total of 992 DNA samples were analyzed with the GeneSeek Genomic Profiler (GGP) 70 K HD porcine genotyping chip. Genotype data was employed to compute genetic diversity, population differentiation and structure, genetic distances, linkage disequilibrium and effective population size. Our results point out several breeds, such as Turopolje, Apulo Calabrese, Casertana, Mora Romagnola and Lithuanian indigenous wattle, having the lowest genetic diversity, supported by low heterozygosity and very small effective population size, demonstrating the need of enhanced conservation strategies. Principal components analysis showed the clustering of the individuals of the same breed, with few breeds being clearly isolated from the rest. Several breeds were partially overlapped, suggesting genetic closeness, which was particularly marked in the case of Iberian and Alentejana breeds. Spanish wild boar was also narrowly related to other western populations, in agreement with recurrent admixture between wild and domestic animals. We also searched across the genome for loci under diversifying selection based on F Pig industry is mainly based on a limited number of cosmopolitan lean breeds which have been extensively used for breeding improvement. These highly selected breeds are raised in intensive production systems, focused on maximizing productivity, and supplying the market with fresh pork. Besides, many local, less performing breeds exist, although some of them are nowadays close to extinction. These traditional breeds are usually associated with local forms of pig husbandry and their meat is used for the production of high-quality and niche products. The Iberian pig, raised in the South-West of the Iberian Peninsula, is probably the most representative local pig breed, although many others are reared in European countries. Common characteristics of these breeds are a good environmental adaptation, rusticity, low muscle mass deposition and high adipogenic potential and, in many cases, superior meat quality traits2.Pork is the most widely consumed meat worldwide3.Conservation of small local breeds is mainly conditioned by their economic relevance but also depends on socio-cultural value, adaptation to local agro-climatic conditions, contribution to the development of local communities and marginal areas, and scientific importance. Efficient utilization of local breeds is needed and for this goal, technological advances, growing knowledge and innovative ideas founded on scientific research must be developed. The genetic characterization of these resources is a preliminary step for the development of conservation programs and to boost local breed promotion, and their sustainable use5 or Casertana7, many other autochthonous breeds have not been analyzed in detail yet and are considered untapped genetic resources. Recently, the diversity at several relevant candidate gene polymorphisms has been evaluated in twenty local European pig breeds8, providing information about the segregation of interesting markers for breeding or traceability10 purposes and giving some first insights into the genetic structure of these populations. Nevertheless, genetic characterization of animal breeds is usually addressed with the analysis of neutral markers like microsatellites or SNPs, as recommended by FAO11. High density SNP panels help to investigate genome wide diversity with a higher resolution. Dense SNP panels can be applied to a variety of genomics studies including inference on population history, structure and admixture12, estimation of effective population size5, QTL mapping strategies13 and whole genome association studies14 and genomic selection15. Also, comparative genomic diversity enables us to explore the degree of genomic variation and linkage disequilibrium (LD) among pig breeds. This as well helps to detect genomic regions that have been subject to selective sweeps in different pig populations16.Despite a few whole genome studies have been carried out for some European local pig breeds, such as the Iberianhttps://treasure.kis.si), a multidisciplinary European Union funded project pointing toward the development of sustainable pork chains in several European local pig breeds.In this study, we analyzed genomic diversity of 20 European local pig breeds: Black Slavonian and Turopolje (Croatia), Basque and Gascon (France), Schwäbisch-Hällisches Schwein (Germany), Apulo-Calabrese, Casertana, Cinta Senese, Mora Romagnola, Nero Siciliano and Sarda , Lithuanian indigenous wattle and Lithuanian White old type (Lithuania), Alentejana and Bísara , Moravka and Swallow-Bellied Mangalitsa (Serbia), Krškopolje pig (Slovenia) and Iberian and Majorcan Black (Spain). The genotyping information from a high density SNP chip has been employed to assess genomic diversity and structure and to identify selection signatures. This work is framed within the TREASURE project  were successfully genotyped with the GeneSeek ® Genomic Profiler (GGP) 70 K HD Porcine chip . The sample sizes of each analyzed population are included in Table 17. The most widely used Illumina 60 K chip was designed and validated using samples from Berkshire, Duroc, Hampshire, Landrace, Large White, Meishan, Pietrain, Synthetic lines (Large White and Piétrain) and wild boar17. The GeneSeek ® GGP Porcine HD Genomic Profiler used in the present study is an improved version of the latter one, which was designed to include the most informative SNPs from the Porcine60K chip, according to findings in the same major commercial breeds, and that was complemented with new SNPs to improve the coverage of the chromosomes and the telomere regions, to better account for recombination18. In spite of the ascertainment bias implicit in the use of SNP chips, previous results have shown that these tools provide reliable estimates of genomic diversity for comparative studies between European populations, even in local breeds19.In general, the informativity of the SNP chip was moderate in most of the studied breeds, which is not unexpected as these local breeds have not been considered for the design of commercial porcine chipsO) and expected (HE) heterozygosity ranged from 0.195 (Turopolje) to 0.363 (Krškopolje) and from 0.187 (Turopolje) to 0.382 (Sarda), respectively  and 0.303 (±0.054), respectively. These heterozygosity values are considerably lower than those reported previously for European cosmopolitan and Chinese pig breeds23, which ranged from 0.30–0.40 to 0.60–0.70 with an average of about 0.5, and similar to those reported for some local breeds19. The lowest heterozygosity values observed in Turopolje are in agreement with a previous study in which microsatellites were employed to assess the genetic diversity and population structure in eight populations corresponding to Balkan pig breeds24. In addition, Lithuanian indigenous wattle shows the smallest (−0.066) inbreeding coefficient of an individual relative to the subpopulation (FIS) while Apulo Calabrese showed the highest one (0.138) . Negative values indicate random mating among the individuals of the subpopulations but do not necessarily imply lower values of the total inbreeding coefficient which takes into account the accumulated inbreeding along the generations25.Genetic variability parameters for the analysed populations are presented in Table 20. The reason for this could be due to the small effective population size: in some of the breeds, only few founders were left at the beginning of the preservation programs2. This can also be the cause for high level of inbreeding observed in some of these breeds. For instance, the highest FIS values obtained in Apulo Calabrese and Casertana are in agreement with their endangered situation and small census27 and similar values were reported recently in an analysis based on candidate gene polymorphisms8.Lack of selection programs and frequent or recurrent admixture, common to these untapped local pig breeds, should presumably lead to a higher degree of genetic diversity. However, the level of genetic variation in our local breeds is in general lower than that in cosmopolitan pig breedsST) for each breed , indicating that most of the genetic variation occurred within populations rather than between breeds, as previously reported for pig populations29. The value obtained is concordant with previous works28, where the averaged FST value calculated between European breeds was 0.134, ranging from 0.021 to 0.209. The overall FST value obtained in the present work  is considerably lower than the one observed in our previous study (0.27)8 performed with an array of selected SNPs. This difference is expected because in the latter study only 39 causal mutations and polymorphisms in candidate genes were used whereas, in the present work, SNP markers across the whole genome and mostly neutral were used6. In addition to this, the distribution of different genetic diversity parameters estimated for each SNP marker is shown in Supplementary Fig. The level of population differentiation can be quantified using the fixation indexes. The fixation Index  to the maximum value of 0.604   was employed to explore the clustering of individuals of different populations. The first three principal components explained 14.26%, 10.92% and 8.49% of the total variation. PCA allowed the visualization of groups formed by individuals belonging to the same breeds Fig. . Moreove8. Next to the Iberian cluster, Spanish Wild Boar and Majorcan Black pigs are also closely grouped, all composing a nucleus of South-Western European populations. A close relatedness between the domestic breeds and the wild relative is observed. This finding is in agreement with the previously proposed recurrent admixture between wild and domesticated animals in Europe33, which might be especially intense in these local breeds, exploited in free-range systems, favoring a long history of genetic exchange with wild boars. The only breed coming from the Iberian Peninsula and being located far away from the south-western cluster is the Bísara breed, for which the separation from Iberian breed had been previously reported12. This is in agreement with its Celtic origin34. Interestingly  Mangalitsa pigs are located in the middle of the western nucleus, quite far away from Moravka (the other Serbian breed), as already evidenced with the NJ tree. Genetic proximity between Hungarian Mangalitsa and Iberian pigs was reported previously by Herrero-Medrano et al.19. Next, four Italian breeds  are clustered in the middle, together with Moravka and Black Slavonian pigs. The right end of the Italian cluster partially overlaps with Bísara and Krškopolje breeds, which are followed by Schwäbisch-Hällisches Schwein and Lithuanian Indigenous wattle, which is in the right end, close but separated from the other Lithuanian breed.Although the individuals are grouped by breeds, there is some overlapping among them, with a big cluster including many breeds. In the left end of this big cluster, Iberian and Alentejana breeds are completely overlapped, in agreement with their genetic closeness and common breeding history35, which may explain its apparently high genetic diversity, despite several bottlenecks occurred since 2003, leading to a critical situation nowadays. The Schwäbisch-Hällisches Schwein breed was originated by crossing local pigs in Württemberg with Chinese pigs, and later by crossbreeding with pigs imported from England2. The creation of Black Slavonian breed, which was a dominant one on the territory of Croatia up to the mid-20th century, resulted from planned crossing between Mangalitsa, Berkshire, Poland China and Large Black  pig37. On the other hand, several breeds have been subjected to crossbreeding with cosmopolitan European breeds carrying Asiatic introgression, such as Krškopolje, which was likely crossed with German Landrace in times when the breed was cast out. Regarding the two Serbian breeds, Moravka was created as a result of unsystematic crossings of the old pig Šumadinka with Berkshire and possibly with Yorkshire38, while no Asian introgression is known for Swallow-Bellied Mangalitsa. This may explain the separation of both breeds observed in the NJ tree and PCA plots, as well as the proximity of Mangalitsa breed to the south-western populations, which are free of Asiatic introgression.Interestingly, the breeds located in the right end of the PCA plots Fig.  are thos40 and detailed information on LD in domesticated animals is important because it is of high utility for fine mapping of genes41. Usually, a substantial extent of LD has been found in domestic species, which may be due to small effective population size in commercial populations. Our study provides an overview of LD patterns against physical distance in 20 European pig breeds and Iberian Wild Boar.Differences in LD among populations result from the differences in population history and demography2 values in distance bins of 0.05, 0.20 and 5.0 Mb for classes a), b) and c), respectively  ranged from 0.305 (Nero Siciliano) to 0.595 (Mora Romagnola); and at long distances (45–50 Mb) r2 values ranged from 0.028 (Iberian) to 0.089 (Casertana). The persistence and strength of LD varied among breeds. Focusing on the domestic breeds, while the LD of Iberian and Alentejana breeds decreased by the half at 0.15 Mb, showing the highest LD decay, the LD of Mora Romagnola and Turopolje decreased by the half at 1.8 and 1.75 Mb, respectively, showing the highest LD persistence. In addition to this, Fig. 2 < 0.2 at distances lower than 2 Mb except Mora Romagnola and Turopolje, which showed r2 < 0.2 at distances lower than 5 Mb. This high level of long LD extent could point out that these breeds have experienced more unbalanced contributions (bottlenecks) or genetic drift compared with the other ones40. Similar r2 values for all the distances were observed for Iberian and Alentejana breeds, supporting the genetic closeness of these breeds already described above. Wild Boar showed the lowest extent of LD in agreement with previous findings28 and as expected for an outbred and non-admixed population. In a previous work44, European pig breeds showed high levels of significant differences in the extent of LD, in agreement with our results.Overall rces Fig. . As expe2 estimates for short distances (0.05 Mb) were averaged by autosomes in all the breeds (Supplementary Table 2 = 0.728) and SSC10 , respectively.Pairwise rances 0.0 Mb were 2 estimates between all pairs within 50 Mb were computed to estimate Ne across 50 generations  and Mora Romagnola and Turopolje were the breeds with the lowest Ne values . Table e (89.18), and Casertana the lowest value (9.44).Synteny rons Fig. –26 using46 recommended an effective population size of 100 in order to maintain the genetic diversity of a population, which is not accomplished in any of the populations analysed in the present work. Our findings further confirm the need for conservation strategies for many of the studied breeds. The most extreme cases are Casertana, Apulo Calabrese, Turopolje, Mora Romagnola and both Lithuanian pig breeds, for which conservation efforts are currently being undertaken49.MeuwissenIn fact, most local breeds are characterized by having small effective population sizes, which affects their diversity, and leads to high levels of LD and a high proportion of SNPs with fixed alleles. In general, breeds showing the highest levels of LD were those with the lowest effective population size and higher inbreeding .ST index was used in order to detect genomic regions that could be involved in domestication, breed pattern establishment or selective breeding. A genome-wide scan of divergent genomic regions was carried out through the estimation of Wright’s FST at each marker as a measure of genetic differentiation. Candidate regions to diversifying selection were identified as those in the 99th percentile of the empirical distributions of sliding windows , lipid, carbohydrate and protein metabolism , growth and development , cellular homeostasis (ATG5), locomotor behavior  and response to nutrient (BCKDHB) were identified. The region located on SSC8 (100.93–101.74) overlapped in seven breeds  and in Wild Boar and contained genes involved in growth and reproduction. The breeds with the highest number of overlapped regions (with five or more breeds) were Alentejana and Iberian in addition to Wild Boar (12 regions), whereas the breed with the lowest number was Mora Romagnola, in agreement with a specific genetic differentiation in this breed, also highlighted in the PCA analyses.A total of 19 genomic regions overlapped in five or more pig groups (breeds and/or wild boars) on chromosomes SSC1, SSC2, SSC6, SSC7, SSC8 and SSC13 , Gascon (SSC13), Iberian (SSC15), Lithuanian Indigenous wattle (SSC4), Swallow-Bellied Mangalitsa (SSC2) and Mora Romagnola (SSC1). This is in agreement with the large repertoire of functional olfactory receptor genes in pigs, the fast evolution of these genesACOX1 and CPT1A, both involved in fatty acid metabolism are identified. NFKBIA and PPARGC1B which have both been associated with backfat thickness in pigs53 are detected in Krškopolje and Cinta Senese breeds, respectively. DECR1, a positional candidate gene for the first fatness QTL detected in pigs on SSC455, is observed in a potentially selected region in Gascon breed. DLK1, a gene with a fundamental role in muscle growth and fat deposition56, is detected in Majorcan Black. LPIN1, which has been associated with obese pig phenotypes57, is detected in Turopolje breed. Taste receptor genes play a fundamental role in survival through the identification of dietary nutrients or potentially toxic substances, being linked to eating behavior and adaptation to specific geographical locations and diets58 and potentially related to growth and fat deposition59. Among this gene family, the TAS2R16 gene was detected in a selection signature in the Turopolje breed. Genes involved in the endocrine regulation of growth and insulin signalling, are also observed: IRS1 is detected in Casertana; GAL and GALR2 in Basque, and members of the insulin like growth factor binding protein gene family are detected in Black Slavonian. These genes code for signalling molecules that integrate and coordinate numerous biologically key extracellular signals within the cell. Some of them are intermediate of the insulin signalling, with a key role in growth, fatness and energy homeostasis61.Also, candidate genes involved in relevant metabolic functions associated with the adipogenic phenotype of our breeds are identified within the putative selected regions. For instance, in the Basque breed, the genes HEDTC2 and IDE in Alentejana; USP54 in Casertana; CAPN10, RNPEPL1 in Iberian; PSMA6 in Krškopolje, CTSV in Turopolje, or UBE4B, RNF150 and UBE2E1 detected in 5 or more breeds simultaneously  is located very close to PPARD gene (31.22–31.29 cM), related to ear morphology, fat deposition and growth, and detected previously as being located in a differentiated genomic region between European breeds and Wild Boar64.Regarding Wild Boar-specific selection signatures, only three regions were detected. Two of them are located in SSC7, an autosome that has been repeatedly shown to be associated with domestication and behavior-related traits in QTL and GWAS studies64. In these studies, as well as in the present one, genes mapped to these regions can be considered as candidates under selection in pig breeds. Some common biological functions have been detected in different works, such as olfaction, growth or muscle development70. Nevertheless, when comparing different works, variable regions and genes have been observed probably due to differences in the breeds analyzed, statistical methods, SNP density or sample size. Especially, domestic pigs under different evolution and production conditions show different selection signatures and in our case all tested populations are locally produced breeds, which have not been selected for lean meat content, muscularity or enhanced reproduction. Thus, in a differentiation analysis among those breeds, expected signatures may be weaker than those observed in commercial and highly selected genotypes, or more related to domestication and breed standards establishment than actual artificial selection processes.In previous works analyzing different commercial and traditional pig populations, a number of regions showing between-breed signatures of selection has been identifiedThe obtained results were useful for the characterization of the genomic diversity of autochthonous European pig breeds. Results highlighted the genetic closeness among several of these domesticated breeds, and with their wild ancestor, as well as clear differentiation of some other ones and confirm the need of conservation programs to protect their genetic pools. Linkage disequilibrium patterns and extent have been determined at the genome level for a wide repertoire of European traditional breeds, showing potential effects of admixture and inbreeding. Putative signals of selection were detected for regions containing genes involved in growth, muscle development, reproduction, metabolism, behavior and sensory perception. Our findings improve the knowledge about the genome biology of European local pig breeds, and provide candidate genes for relevant traits, as well as useful information for future conservation, association or selection approaches.Experts of each country, including personnel from breeding organizations and herd books, selected the animals to be included in the analyses in order to get a representative sampling of each breed. Selection of individuals for sampling was performed by avoiding highly related animals , balancing between sexes and prioritizing adult individuals or at least animals with adult morphology. Blood samples were obtained from 39 to 54 individuals from each one of the 20 local pig breeds included in the study: Black Slavonian and Turopolje (Croatia), Basque and Gascon (France), Schwäbisch-Hällisches Schwein (Germany), Apulo-Calabrese, Casertana, Cinta Senese, Mora Romagnola, Nero Siciliano and Sarda , Lithuanian indigenous wattle and Lithuanian White old type (Lithuania), Alentejana and Bísara , Moravka and Swallow-Bellied Mangalitsa (Serbia), Krškopolje pig (Slovenia) and Iberian and Majorcan Black (Spain). Besides, seven European wild boars were employed as outgroup. Specialized professionals from each institution that provided animal material obtained blood samples following standard routine monitoring procedures and guidelines, at farm or at slaughter. No procedures with animals were performed that would demand ethical protocols according to Directive 2010/63/EU (2010) and blood samples were obtained as a general breeding procedure or previously collected DNA only reused here. A total of 992 DNA samples were genotyped.71.The genomic DNA was extracted from leukocytes present in 8–15 mL of peripheral blood, collected in Vacutainer tubes containing 10% 0.5 M EDTA  at pH 8.0. The extraction was performed using either a standardized phenol-chloroform, high-salt method or a commercial kitSamples were genotyped with the GeneSeek ® GGP Porcine HD Genomic Profiler v1 , which includes 68,516 SNPs evenly distributed with a median of 25 kb gap spacing and sharing 42,372 markers with Illumina porcine SNP60 chip. The average genotyping call rate was 0.94.72. SNPs with MAF lower than 0.01 or more than 10% missing genotypes were excluded from the analyses in a preliminary filter to inspect the distribution of MAF across the genotyped SNPs. In addition, an individual call rate threshold was set to 95% and ten samples  were removed for further analyses.Genotype quality control (QC) and data filtering were performed using PLINKO) and expected heterozygosity (HE), inbreeding coefficient of an individual (I) relative to the subpopulation (S) (FIS), fixation index (FST) and inbreeding coefficient of an individual (I) relative to the total (T) population (FIT), heterozygosity index based on observed heterozygosity in individuals within breeds (HI) based on expected heterozygosity in subpopulation (HS) and based on expected heterozygosity for overall breeds (HT). Calculations were made with VCFtools software73. Nei’s genetic distances12 were calculated in R74 environment. Pairwise distances were used to build a NJ tree with the nj function belonging to the ape75 library in R. In addition, population structure was inspected trough PCA analyses performed with DISSECT software tool76.A total of 51,219 SNPs mapped on the 18 autosomes on Sus Scrofa 11.1 were used to compute, for the 20 studied breeds, the following indicators of genetic diversity: observed (H−7) and unmapped or mapped in sexual chromosomes were excluded from LD analysis. This QC filtering was carried out independently for each breed and the number of SNP used is showed in Supplementary Table 2 was estimated for all marker pairs less than 50 Mb for each population and autosome independently using PLINK. To plot LD vs physical distance between markers, following Saura et al.4, we divided SNP pairs into three distance classes, (a) 0 to 2 Mb, (b) 2 to 5 Mb and (c) 5 to 50 Mb. Distance bins of 0.05, 0.20 and 5.0 Mb were used for classes (a), (b) and (c), respectively, and average r2 values for each bin were plotted against physical distance. Sample sizes were similar for all the breeds except for Wild Boar. As sample size can have an influence on LD estimation, a correction for sampling size was used to estimate r2 in Wild Boar as follows: (r2 − 1/N) (1 − 1/N)77.Markers with MAF lower than 0.05, with more than a 10% of missing values, significantly deviating from Hardy-Weinberg equilibrium (P < 8.27 × 10e) for each population were computed using the relationship between LD and Ne according to the following equation78:c is the distance between SNPs (Morgans), Ne is the sample size and absence of mutation was assumed  in at least one of the studied breeds were removed. A total of 828 SNPs was extracted from the subset of 51,219 SNPs used to compute genetic diversity parameters. Pairwise Wright’s FST81 were estimated as a measure of genetic differentiation according to the method described in Wilkinson et al.64. For each breed, a total of 21 breed-pairwise comparisons at each SNP were obtained and they were averaged to get overall FST for each SNP per breed. FST values were averaged in sliding windows of 13 SNPs centred at the 7th SNP which determined the genomic location of the window. Regions in the 99th percentile of the empirical distributions of windows per breed were defined as candidate regions to genetic differentiation. Genes were annotated with Biomart tool82.Hardy-Weinberg equilibrium was inspected individually in all breeds. SNPs significantly deviating from Hardy-Weinberg equilibrium (P < 8.27 × 10Supplementary material 1Supplementary material 2Supplementary material 3Supplementary material 4


In mammalian cells, >25% of synthesized proteins are exported through the secretory pathway. The pathway complexity, however, obfuscates its impact on the secretion of different proteins. Unraveling its impact on diverse proteins is particularly important for biopharmaceutical production. Here we delineate the core secretory pathway functions and integrate them with genome-scale metabolic reconstructions of human, mouse, and Chinese hamster ovary cells. The resulting reconstructions enable the computation of energetic costs and machinery demands of each secreted protein. By integrating additional omics data, we find that highly secretory cells have adapted to reduce expression and secretion of other expensive host cell proteins. Furthermore, we predict metabolic costs and maximum productivities of biotherapeutic proteins and identify protein features that most significantly impact protein secretion. Finally, the model successfully predicts the increase in secretion of a monoclonal antibody after silencing a highly expressed selection marker. This work represents a knowledgebase of the mammalian secretory pathway that serves as a novel tool for systems biotechnology. The secretory pathway is used in the production of most biopharmaceuticals, but the associated biosynthetic costs are little understood. Here, the authors integrate the core secretory pathway into genome-scale metabolic models of human, mouse, and CHO cells, enabling in silico analysis. In mammals, these include at least 2641 secreted proteins  and >5500 membrane proteins2. For any given biotherapeutic, different machinery in the secretory pathway may be needed, and each step can exert a non-negligible metabolic demand on the cells. The complexity of this pathway, however, makes it unclear how the biosynthetic cost and cellular needs vary for different secreted proteins, each of which exerts different demands for cellular resources. Therefore, a detailed understanding of the biosynthetic costs of the secretory pathway could guide efforts to engineer host cells and bioprocesses for any desired product. The energetic and material demands of the mammalian secretory pathway can be accounted for by substantially extending the scope of metabolic models. Indeed, recent studies have incorporated portions of the secretory pathway in metabolic models of yeast5. Furthermore, Lund et al.6 reconstructed a genetic interaction network of the mouse secretory pathway and the unfolded protein response and analyzed it in the context of CHO cells. However, such a network does not encompass a stoichiometric reconstruction of the biochemical reactions involved in the secretory pathway nor it is coupled to existing metabolic networks of mammalian cells.The secretory pathway consists of a complex series of processes that predominantly take place in the endoplasmic reticulum (ER), Golgi apparatus, and the endomembrane system. This pathway is particularly important in biotechnology and the biopharmaceutical industry, since most therapeutic proteins are produced in mammalian cell lines such as HEK-293, PerC6, NS0, and Chinese hamster ovary (CHO) cells, which are capable of folding and adding the necessary post-translational modifications (PTMs) to the target producthttps://github.com/LewisLabUCSD/MammalianSecretoryRecon.Here, we present the first genome-scale stoichiometric reconstructions and computational models of mammalian metabolism coupled to protein secretion. Specifically, we constructed these for human, mouse, and CHO cells, called RECON2.2s, iMM1685s, and iCHO2048s, respectively. We first derive an expression for computing the energetic cost of synthesizing and secreting a product in terms of molecules of ATP equivalents per protein molecule. We use this expression and analyze how the energetic burden of protein secretion has led to an overall suppression of more expensive secreted host cell proteins in mammalian cells. Given its dominant role in biotherapeutic production, we further focus on the biosynthetic capabilities of CHO cells. We then demonstrate that product-specific secretory pathway models can be built to estimate CHO cell growth rates given the specific productivity of the recombinant product as a constraint. We identify the features of secreted proteins that have the highest impact on protein cost and productivity rates. Finally, we use our model to identify proteins that compete for cell resources, thereby presenting targets for cell engineering. Through this study we demonstrate that a systems-view of the secretory pathway now enables the analysis of many biomolecular mechanisms controlling the efficacy and cost of protein expression in mammalian cells. We envision our models as valuable tools for the study of normal physiological processes and engineering cell bioprocesses in biotechnology. All models and data used in this study are freely available at 7, GPI anchor attachment signals8, and experimentally measured the number of N-linked glycans in the CHO proteome and integrated published numbers of O-linked glycans in CHO proteomic data9. Across the CHO secretome, protein synthesis cost varies substantially, and recombinant products are on average more expensive . This imposes a significant burden to the secretory machinery of CHO cells, which typically express much less expensive endogenous proteins.In any cell, the secretory machinery is concurrently processing thousands of secreted and membrane proteins, which all compete for secretory pathway resources and pose a metabolic burden. To quantify this burden, we estimated the energetic cost of synthesizing and/or secreting 5641 and 3538 endogenous proteins in the CHO and human secretome and membrane proteome in terms of total number of ATP equivalent molecules consumed (see Methods). These protein costs were compared to the cost of five recombinant proteins commonly produced in CHO cells Fig. . To refiive Fig. . For exaWith the broad range of biosynthetic costs for different proteins, we wondered if gene expression in mammalian cells that are tasked with high levels of protein secretion have been influenced by the ATP cost of secreted proteins. That is, have these secretory cells suppressed their protein expression to more efficiently allocate nutrients? To test this, we first looked at CHO cells, which have undergone extensive selection to obtain cells that secrete recombinant proteins at high titer, and then compared different human tissues with a range of secretory capacity.12 and compared translation of each transcript against the ATP cost of the associated secreted protein (see Methods). Indeed, there was a significant negative correlation of −0.43  between ribosomal occupancy and ATP cost during early exponential growth phase of culture  data from a recombinant CHO cell lineure Fig. . Wonderi1. For all RNA-Seq datasets in the HPA, there was a negative correlation between mRNA expression levels and ATP cost  contains a relatively high number (17) of disulfide bonds. In conclusion, there is a clear preference in CHO and native secretory tissues to suppress the expression and translation of proteins that are costly to synthesize, fold, and secrete.To evaluate if this is a general trend in mammalian secretory cells, we analyzed RNA-Seq data from human tissues and immortalized cell lines in the Human Protein Atlas (HPA)ost Fig. . Interes15, iMM141516, iCHO176617). Following the naming convention of their metabolic counterparts, we named these new metabolic-secretory reconstructions as follows: iMM1685s, iCHO2048s, and Recon 2.2s, which account for 1685, 2048, and 1946 genes, respectively. A detailed list of the components, reactions and the associated genes can be found in the Supplementary Data We mapped out the core processes involved in the synthesis of secreted and membrane proteins in mammalian cells . This included 261 components (gene products) in CHO cells and 271 components in both human and mouse. The components are involved in secretory reactions across 12 subsystems  and specific productivity (qP), given the same measured glucose and amino acid uptake rates for each model17 . For example, the synthesis of a mAb requires the use of multiple processes and consumes several different metabolites, such as amino acids for protein translation, redox equivalents for forming disulfide bonds, ATP equivalents for vesicular transport, and sugar nucleotides for protein glycosylation Fig. . Therefo–1) and specific productivity  as a Pareto optimal curve for each protein . We found that the secretory pathway had non-negligible costs on most proteins , GPI anchors (p = 0.0216), transmembrane domains (p = 0.0326), and proteins destined to the ER lumen (p = 0.0142), the Golgi membrane (p = 0.0065), or the plasma membrane  using iCHO2048s and its parent metabolic reconstruction iCHO176612 demonstrated that a CHO-DG44 cell line producing an antiviral mAb19 also expressed high levels of the neoR selection-marker gene  and 6 (late phase) of culture, respectively  increased by 18% when neoR production is eliminated 6 recently reconstructed a comprehensive genetic network of the mouse secretory pathway. By comparing the mouse and CHO-K1 genomes and mapping CHO gene expression data onto this network, the authors identified potential targets for CHO cell engineering, demonstrating the potential of systems biology to interrogate and understand protein secretion in animal cells. This genetic network reconstruction, although useful for contextualizing omics data , is not set up for simulations of protein production, nor integrated with additional cellular processes such as metabolism. Therefore, our work is complementary in that it allows one to also to quantify the cost and cellular capacity for protein production by delineating the mechanisms of all biosynthetic steps and bioenergetic processes in the cell.Efforts have been underway to enumerate the machinery needed for protein production. For example, Lund et al.20.Here, we presented the first genome-scale reconstruction of the secretory pathway in mammalian cells coupled to metabolism. We connected this to current metabolic networks, yielding models of protein secretion and metabolism for human, mouse and CHO cells. These models compile decades of research in biochemistry and cell biology of higher eukaryotes and present it in a mathematical model. Using our model, we quantitatively estimated the energetic cost of producing several therapeutic proteins and all proteins in the CHO cell and human secretomes. We also identified factors limiting the secretion of individual products and observed that these depend on both the complexity of the product and the composition of the culture media. Furthermore, by integrating ribosomal profiling data with our model we found that CHO cells have selectively suppressed the expression of energetically expensive secreted proteins. Expanding upon this observation, we demonstrated that specific productivities can be predictably increased following the knock-down of an energetically expensive, non-essential protein. Furthermore, consistent with this, we have recently shown more than 50% reductions in total host cell protein production, along with increases in mAb titer when deleting 14 highly abundant proteins in CHO cells. Future studies will likely further explore how much of the CHO cell proteome can be deleted to further enhance recombinant protein secretion6 . These could be included as energetic costs associated with building and maintaining the secretory machinery ; protein stability and turnover rates39; solubility constraints40 and molecular crowding effects41. As these are captured by the models in a protein product-specific manner, predictions of protein production capacity will improve, and the models could provide further insights for cell engineering for biotechnology or to obtain a deeper understanding of mechanisms underlying amyloid diseases. Finally, a simplification of our secretory model is that it only computes the bioenergetic cost of synthesizing and attaching single representative N- and O-linked glycans to secreted proteins . Thus, an immediate potential expansion of our secretory model would involve coupling it to existing computational models of protein glycosylation43. For example, given an N-glycan reaction network that captures the glycoform complexity of a target protein44, one could build secretory reactions for the specific glycoforms of interest and compute the metabolic demands associated with each of them to identify potential targets and nutrient supplementations for glycoengineering.It is important to note that while our models capture major features of secreted proteins, there are additional PTMs , pathway machinery , and cell processes that could possibly be captured in further expansions of the modeling framework45. To facilitate further use of these models, we provide our code and detailed instructions on how to construct protein-specific models in the Jupyter Notebooks available at https://github.com/LewisLabUCSD/MammalianSecretoryRecon.In conclusion, the results of our study have important implications regarding the ability to predict protein expression based on protein-specific attributes and energetic requirements. The secretory pathway models here stand as novel tools to study mammalian cells and the energetic trade-off between growth and protein secretion in a product- and cell-specific manner. We presented algorithms that provide novel insights with our models, and expect that many other methods can be developed to answer a wide array of questions surrounding the secretory pathway, as seen for metabolism3 were used as a starting reference. To build species-specific models, orthologs for human, mouse and the Chinese hamster were identified and used, while yeast components and subsystems that are not present in the mammalian secretory pathway were removed. Additional subsystems were added when unique to higher eukaryotes, such as the calnexin-calreticulin cycle in the ER46. These were constructed de novo and added to the reconstruction. The databases and literature were then consulted to identify the remaining components involved in each subsystem of the mammalian secretory pathway. Since most components in the mammalian secretory pathway have been identified in mouse and human, BLAST was utilized to identify the corresponding Chinese hamster orthologs by setting human as the reference organism and a cutoff of 60% of sequence identity. See A list of proteins and enzymes in the mammalian secretory pathway was compiled from literature curation, UniProt, NCBI Gene, NCBI Protein and CHOgenome.org (see Supplementary Data 7) and GPI anchors (GPI-SOM8). Finally, additional information on the number of O-linked glycosylation sites of certain proteins were obtained from experimental data in previous studies47. The PSIMs of the CHO and human secretomes are a subset of the full PSIM and contains only the proteins with a signal peptide (predicted or confirmed in Uniprot). The distribution of all PTMs across the human, mouse and CHO proteomes can be found in Jupyter Notebook D. For analyzing secretomes, a total of 3378 human proteins were picked based on the presence of a signal peptide in their sequence according to their annotation in the UniProt database. Similarly, 5641 CHO proteins were picked based on the presence of a signal peptide in their sequence and/or for being localized in the cell membrane according to the UniProt database.The PSIM  were lysed, denatured, reduced, alkylated and digested by trypsin. Desalted peptides were incubated with 10 mM sodium periodate in dark for 1 h before coupling to 50 μL of (50% slurry) hydrazide resins. After incubation overnight, non-glycosylated peptides were washed with 1.5 M NaCl and water. The N-glycosylated peptides were released with PNGaseF at 37 °C and desalted by using a C18 SepPak column. Strong cation exchange (SCX) chromatography was used to separate the sample into 8 fractions. Each fraction was analyzed on an LTQ-Orbitrap Velos  mass spectrometer. During the mass spectrometry data analysis, carbamidomethylation was set as a fixed modification while oxidation, pyroglutamine, and deamidation were variable modifications.48) and all other constraint-based analyses were done using the COBRA toolbox v2.049 in MATLAB R2015b and the Gurobi solver version 6.0.0. The analyses in Figs. qp) while maintaining a growth rate (in units of inverse hours) of 0.01. Finally, since the exact glycoprofiles of most proteins in CHO are unknown and some even change over time in culture50, we simplified our models by only adding the core N-linked and O-linked glycans to the secreted proteins.We wrote a Jupyter Notebook in Python (see Jupyter Notebook A) that takes a row from the PSIM as input to produce an expanded iCHO2048s, Recon 2.2s, or iMM1685s metabolic model with the product-specific secretory pathway of the corresponding protein. Flux balance analysis  supplemented with 8 mM l-Glutamine (Lonza) and 1 μL per mL anti-clumping agent (Life Technologies), in 250 mL Erlenmeyer shake flasks. Cells were incubated in a humidified incubator at 37 °C, 5% CO2 at 120 rpm. Viable cell density and viability were monitored every 24 h for 7 days using the NucleoCounter NC-200 Cell Counter (ChemoMetec). Daily samples of spent media were taken for extracellular metabolite concentration and titer measurements by drawing 0.8 mL from each culture, centrifuging it at 1000 × g for 10 min and collecting the supernatant and discarding the cell pellet.Two isogenic CHO-S cell lines  adapted to grow in suspension, one producing Enbrel (Etanercept) and the other producing human plasma protease C1-inhibitor (C1INH), were seeded at 3 × 10To quantify Enbrel and C1INH titers, biolayer interferometry was performed using an Octet RED96 . ProA biosensors (Fortebio 18–5013) were hydrated in phosphate-buffered saline (PBS) and preconditioned in 10 mM glycine pH 1.7. A calibration curve was prepared using Enbrel (Pfizer) or C1INH at 200, 100, 50, 25, 12.5, 6.25, 3.13, 1.56, 0.78 μg per mL. Culture spent media samples were collected after centrifugation and association was performed for 120 s with a shaking speed of 200 rpm at 30 °C. Octet System Data Analysis 7.1 software was used to calculate binding rates and absolute protein concentrations.4+), and glutamine in spent media were measured using the BioProfile 400 . Amino acid concentrations were determined via High-Performance Liquid Chromatography using the Dionex Ultimate 3000 autosampler at a flow rate of 1 mL per minute. Briefly, samples were diluted 10 times using 20 μL of sample, 80 μL MiliQ water, and 100 μL of an internal amino acid standard. Derivatized amino acids were monitored using a fluorescence detector. OPA-derivatized amino acids were detected at 340ex and 450em nm and FMOC-derivatized amino acids at 266ex and 305em nm. Quantifications were based on standard curves derived from dilutions of a mixed amino acid standard (250 ug per mL). The upper and lower limits of quantification were 100 and 0.5 μg per mL, respectively.The concentrations of glucose, lactate, ammonium . The energetic cost  of secreting each protein (length L) was computed using the following formulas and assumptions.Energy cost of translation: For each protein molecule produced, 2 L ATP molecules are cleaved to AMP during charging of the transfer RNA with a specific amino acid; 1 GTP molecule is consumed during initiation and 1 GTP molecule for termination; L-1 GTP molecules are required for the formation of L-1 peptide bonds; L-1 GTP molecules are necessary for L-1 ribosomal translocation steps. Thus, the total cost of translation (assuming no proofreading) is 4 L.Average cost of signal peptide degradation: On average, signal peptides have a length of 22 amino acids. Thus, the average cost of degrading all peptide bonds in the signal peptide is 22. This average cost was assigned to all proteins analyzed.Energetic cost of translocation across the ER membrane: During activation of the translocon, two cytosolic GTP molecules are hydrolyzed. From there, a GTP molecule bound to the folding-assisting chaperone BiP is hydrolyzed to GDP for every 40 amino acids that pass through the translocon pore46. Thus, the cost of translocation is (L ÷ 40) + 2.Energetic cost of vesicular transport and secretion: We used published data53 (see Supplementary Data VP (nm3) that is directly proportional to its molecular weight MW54:VCOPII is:All models were constrained using different sets of experimental uptake rates, which can be found in Supplementary Data 12 were used to quantify the ribosomal occupancy of each transcript in CHO cells. A cutoff of 1 RPKM was used to remove genes with low expression . We used Spearman correlation to assess the variation of expression levels with respect to protein ATP cost.Ribosome-profiling data12. From the same cultures, we obtained further cell dry-weight and metabolomic data from spent culture medium for this study. The mCADRE algorithm56 was used to construct a DG44 cell line-specific iCHO2048s model. The specific productivity and the RPKM values of the secreted IgG were used to estimate the translation rate for the neoR selection-marker gene. We assumed that the flux (in units of mmol per gram dry-weight per hour) through the neoR translation reaction (vneoR) should be proportional to that of the IgG translation rate  and related to their expression ratios .neoR peptide translation (which is expressed in the cytosol and is not processed in the secretory pathway) was added to construct a neoR-specific iCHO2048s model. Uptake and secretion rates of relevant metabolites on days 3 and 6 of cell culture were used to constrain our model. As recombinant proteins represent 20% of total cell protein57, we scaled the coefficients of all 20 amino acids in the model’s biomass reaction accordingly . We then used FBA to predict the specific productivity of IgG with or without neoR.Ribosome-profiling data, specific productivity, product sequence, and growth rates of an IgG-producing CHO-DG44 cell line were obtained from a previous publicationFor cell dry-weight measurements, six tubes containing 2 mL of culture samples of known viable cell density and viability were freeze dried, weighed, washed in PBS, and weighed again. The difference in weight was used to calculate the mass per cell. The procedure resulted in an average cell dry-weight of 456 pg per cell. As a simplification, we assumed that cell dry-weight does not significantly differ from this average measured value during culture and thus was used when computing flux distributions in all simulations.23. When rates were not explicitly stated in the studies we consulted, we used a method we developed previously27. Briefly, appropriate viable cell density, titer, and metabolite concentration plots were digitized using WebPlot Digitizer software and we computed the corresponding rates as follows:Supplementary Data vx of metabolite x (in units of millimoles per gram dry-weight per hour):Growth rate (in units of inverse hours):Further information on research design is available in the Supplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Reporting Summary


In this work, for the first time, the volatile organic compound (VOC) emissions from carbonized refuse-derived fuel (CRDF) were quantified on a laboratory scale. The analyzed CRDF was generated from the torrefaction of municipal waste. Headspace solid-phase microextraction (SPME) and gas chromatography-mass spectrometry (GC-MS) was used to identify 84 VOCs, including many that are toxic, e.g., derivatives of benzene or toluene. The highest emissions were measured for nonanal, octanal, and heptanal. The top 10 most emitted VOCs contributed to almost 65% of the total emissions. The VOC mixture emitted from torrefied CRDF differed from that emitted by other types of pyrolyzed biochars, produced from different types of feedstock, and under different pyrolysis conditions. SPME was a useful technology for surveying VOC emissions. Results provide an initial database of the types and relative quantities of VOCs emitted from CRDF. This data is needed for further development of CRDF technology and comprehensive assessment of environmental impact and practical storage, transport, and potential adoption of CRDF as means of energy and resource recovery from municipal waste. Biochar is a fine-grained product characterized by a high content of organic carbon and low susceptibility to decomposition. It is obtained in the process of torrefaction, pyrolysis, or gasification of plant biomass, biodegradable waste, and sewage sludge . The EurMunicipal waste is used increasingly as a resource to recover energy and materials via thermal processes. The direction being actively pursued in the field of torrefaction and pyrolysis of municipal waste is the conversion of the fraction of combustible fraction of waste  into high-calorific solid fuel (CRDF) as a ‘Waste-To-Carbon’ waste management strategy ,9.One of the challenges related to the development of torrefaction and pyrolysis technology for municipal waste is the expected potential environmental impact of biochar through emissions of volatile organic compounds (VOCs). The VOCs are defined as any organic compound with an initial boiling point less than or equal to 250 °C measured at a standard pressure of 101.3 kPa  VOCs wasThe problem of VOCs emissions from biochar was also reported by Taherymoosavi et al. , who anaTo date, published literature on VOC emissions focuses on biochars produced from biomass, mainly via pyrolysis. However, no VOC emissions have been evaluated from biochars produced from municipal waste, and in particular from torrefied RDF, a new potential future fuel source in a circular economy. For this reason, the main purpose of the work was to identify VOCs emitted from carbonized-RDF (CRDF) biochar produced via torrefaction from RDF and quantify their emissions. Information is needed about the types and quantities of VOCs emitted. This, in turn, can address many practical questions about the potential toxicity; storage, transport, and adoption of CRDF as a future energy source.In this work, for the first time, emissions of VOCs from CRDF was studied qualitatively and quantitatively. Qualitative analysis consisted of identifying compounds based on MS spectral database and available literature (Kovats Retention C7-40 Index). The 84 VOCs  have been identified. These compounds belong to various groups such as alcohols , aldehydes, , ketones , aromatic compounds (including toluene and benzene derivatives), polycyclic aromatic hydrocarbons , acids , alkenes , phenols and a large group of heterocyclic compounds (including pyridine and pyrazine with derivatives). The largest (by number) group were derivatives of benzene and naphthalene . The highest density of peak elution of VOCs from the chromatographic column occurred between 7 to 12 min . Most ofThe total mass of VOCs emitted from CRDF was 16.4 mg/kg  based onThe determined composition of the VOCs mixture emitted from CRDF stored in a sealed vessel (this research) is unique because it was likely driven by the type of municipal waste and the process parameters used for its production. However, for illustrative purposes, it is useful to compare with VOCs emitted from other types of biochar. Spokas et al.  reportedIn the present work, only eight compounds were also reported by Spokas et al.  Table 2Table 2. Buss et al.  analyzedThere is little research in literature related to the subject of qualitative and quantitative identification of VOCs emitted from the surface of biochar, especially from biochar produced from municipal solid waste such as CRDF. This is a relatively new topic related to the trend of using torrefaction, and low-temperature pyrolysis of municipal solid waste in recent years. These new trends in municipal solids treatment are being sought as an alternative to both energy production and ‘Waste to Carbon’ utilization . Thus the interest in identifying and mitigating VOC emissions from biochar will likely increase. As biochar VOCs are still not deeply explored, it is required to continue research on the effects of feedstock type and thermal treatment conditions on VOCs formation and emission, especially in the contest on potential harmful effect to workers during biochar storage and transportation and end users.CRDF was produced in the torrefaction process at 260 °C and a 50 min retention time in a batch reactor, according to the procedure described by , which h1)the internal standard—a solution of 2-undecanone at a ratio of 20 μg compound per 20 mL of distilled water;2)water bath with a temperature of 40 °C with glycol;3)manual holder for SPME;4)universal SPME fiber 3-component DVB/CAR/PDMS 50/30 μm coating ;5)10 μL syringe for internal standard addition;6)a laboratory incubator  with a constant temperature of 23 °C.Measurements of VOCs were made using headspace (HS) solid-phase microextraction (SPME) technology for gas extraction and gas chromatography coupled with mass spectrometry (GC-MS)  for analyses. SPME technology combines sampling and sample preparation and is suited for exploratory qualitative and quantitative work on VOC emissions from a wide range of sources such as contaminated soils ,21, decaTo prepare the samples for VOCs emission analysis, the CRDF was pre-treated and ground in a 2SIEL90L2 grinding mill  to homogenize the sample to size <0.5 mm. Next, 10 g of bulk 3 subsamples were placed in a sealed 1000 mL glass vessels. An internal standard, 10 µg of 2-undecanone , was added to the vessels to account for the variability in emissions and to aid VOC quantification. Each sealed sample was stored in a laboratory incubator at a constant temperature of 23 °C for 7 days, after which it was removed for sampling. The VOCs extraction was carried out from the headspace of sealed vessel, by the SPME.After placing the sealed vessel with the sample in a water bath with glycol preheated to 40 °C, a 3-component universal fiber coating (DVB/CAR/PDMS 50/30 μm) was introduced into the vessel headspace. The SPME exposure lasted 20 min, similarly to the types of coatings and extraction times used for VOC emissions from solid, porous matter. The DVB/CAR/PDMS 50/30 μm SPME coating is often recommended and used for exploratory work on VOC emissions from unknown sources ,26,28. Tm/z using electron impact ionization at 70 eV [The separation, identification and quantification of VOCs adsorbed on the fiber was conducted using a GC coupled to a MS detector  with ZB-5  column (30 m × 0.25 µm film ×  0.25 mm i.d.). Chromatographic conditions were performed according to Calin-Sanchez et al. . Scanninat 70 eV . The anaThe VOCs emitted from CRDF samples were identified using three independent analytical methods: retention indices (RI), GC–MS retention times of authentic chemical standards, mass spectra of compounds  and compThe retention index standards used in this study consisted of a mixture of aliphatic hydrocarbons ranging from C-7 through C-40 dissolved in hexane .The use of internal standard enabled quantitative analysis of VOCs. It was carried out using the Mnova MS 12.0.1 software  based on the retention time of individual compounds, through the integration of the peak area of the chromatogram. The percentage ratio of individual VOC was determined. VOC emissions (on per mass of CRDF basis) were estimated based on the recovered internal standard. All raw data were shown as In the analyzed CRDF (biochar) from municipal waste, 84 VOCs have been identified, including many that are toxic, e.g., derivatives of benzene or toluene. The highest emission was measured for nonanal, octanal, heptanal. The top 10 of the most emitted VOCs consisted almost 65% of total emissions. The mixture of emitted from CRDF VOCs differed from those emitted by other types of biochars, produced from different types of feedstock, and under different pyrolysis conditions. SPME provided a useful tool for characterizing VOC emissions from CRDF, a new potential fuel exemplifying the ‘Waste to Carbon’ concept in a circular, zero-waste economy.


Ananas erectifolius) is a promising strong candidate to replace synthetic fibers, such as aramid (Kevlar™), in multilayered armor system (MAS) intended for ballistic protection against level III high velocity ammunition. Another remarkable material, the graphene oxide is attracting considerable attention for its properties, especially as coating to improve the interfacial adhesion in polymer composites. Thus, the present work investigates the performance of graphene oxide coated curaua fiber (GOCF) reinforced epoxy composite, as a front ceramic MAS second layer in ballistic test against level III 7.62 mm ammunition. Not only GOCF composite with 30 vol% fibers attended the standard ballistic requirement with 27.4 ± 0.3 mm of indentation comparable performance to Kevlar™ 24 ± 7 mm with same thickness, but also remained intact, which was not the case of non-coated curaua fiber similar composite. Mechanisms of ceramic fragments capture, curaua fibrils separation, curaua fiber pullout, composite delamination, curaua fiber braking, and epoxy matrix rupture were for the first time discussed as a favorable combination in a MAS second layer to effectively dissipate the projectile impact energy.Composites with sustainable natural fibers are currently experiencing remarkably diversified applications, including in engineering industries, owing to their lower cost and density as well as ease in processing. Among the natural fibers, the fiber extracted from the leaves of the Amazonian curaua plant ( In recent decades, the increasing efficiency of ballistic armors has emerged as a relevant factor in personal and vehicular security, for both civilian and military protection. The search for lighter and stronger armor materials has been increasing in proportion to the escalating power and sophistication in firearms development . ResearcAnanas erectifolius, sharing the pineapple family. It has attracted considerable interest as polymer composite reinforcement [3) in comparison to glass (2.58 g/cm3) and aramid (1.44 g/cm3) synthetic fibers [3/g) is higher than that of glass (~1.4 Gpa·cm3/g) and close to that of aramid (~2.8·Gpa.cm3/g) fibers.Together with ballistic protection, recent works on nano and micro cellulose ,25,26,27orcement ,32,33,34c fibers . In consAs most NLFs applied in polymer composite ,39,40,41In spite of the comparable ballistic performance to a same thickness Kevlar™ laminate as MAS second layer, the integrity of a NLF composite is always questionable. Lower amounts, usually less than 30 vol%, of fiber were found to result in composite shattering ,15,16,17Since the rise of graphene , it has To the knowledge of the authors of the present work, GO has not yet been applied as a coating onto NLFs to improve interfacial shear strength with respect to a polymer composite for armor application. More specifically, as a novel method to provide efficient fiber/matrix interface for impact energy dissipation. Therefore, the objective of this work is, for the first time, to investigate the ballistic performance of 30 vol% graphene oxide coated curaua fiber (GOCF) reinforced epoxy composite, as a MAS second layer against the treat of level III  high velCuraua fibers, shown in Curaua fibers were used in two main conditions, namely: as-received, non-coated fibers (CF), and graphene oxide coated fibers (GOCF). Initially the as-received fibers were subjected to a mechanical treatment using a hard bristle brush for cleaning, separation, and fiber alignment. Then fibers were cut into 150 mm in length and placed in an oven at 80 °C for 24 h until the fiber weight remained stable. This corresponds to the as-received CF used to produce plain composite plates.The GO used in this work was produced by the Hummers Offeman method, modified by Rourke et al. . The CFs3 [3 for the epoxy resin [To fabricate the composite plates, a metal mold with dimensions of 150 × 120 × 12 mm was used. The plates were processed in a SKAY hydraulic press by applying a load of 5 tons for 24 h. For the CF, the density of 0.92 g/cm3  was usedxy resin . The perInterfacial shear strength tests were performed to investigate the influence of GO coating onto curaua fiber in curaua-epoxy composites. For this, the method described by Kelly and Tyson  was usedBallistic tests were carried out to investigate both CF and GOFC composites capacity of dissipating kinetic energy of a high velocity projectile in a MAS. The MAS used in this work consist, of a front layer of ceramic, an intermediate layer made from both the CF and GOCF epoxy composites, Microscopic analyses of the curaua fibers and fractured surface of the investigated composites were performed by scanning electron microscopy (SEM) in a model Quanta FEG 250 Fei microscope operating with secondary electrons between 5 and 10 KV. The energy dispersive spectroscopy (EDS) analyses were performed using a Bruker Nano GmbH XFlash 630M detector.The FTIR technique was used to investigate the possible influences of GO on the functional groups of the curaua fibers, in an IR-Prestige-21 model spectrometer from Shimadzu, using the transmittance method with the KBr insert technique. For all samples, the same mass quantities of 2 mg of fiber and 110 mg of KBr were used.For the analysis by thermogravimetry (TGA), the curauá fibers in CF, GOCF, and its composites were comminuted and placed in aluminum crucible of the TA Instruments, model Q 500 analyzer. Samples were subjected to a heating rate of 10°/min, starting at 30 °C up to 700 °C.The thickness estimation of GO coating was obtained by atomic force microscope in a model Park systems XE7 atomic Force Microscope.−1 for GO in −1 from the spectra. In addition, the shifted location of 2D band, because of the presence of oxygen-containing functional groups, prevents the graphene layer to stack [The Raman spectra of GO is shown in to stack .−1, which is related to the elongation of OH groups present in cellulose and water. The 2916 cm−1 band can be attributed to the symmetrical and asymmetrical stretching (C–H) of the aliphatic chain, 1736 cm−1 corresponding to the acid elongation vibration (C=O); 1430 cm−1  and 1110 cm−1 from the elongation vibration of the ether groups. Other bands refer to the existence of high content of oxygen functional groups on GOCF surface, such as (–C–O–C) and (–C–OOH) [The main absorption bands of the CF fiber spectrum can be seen as: 3379 cm(–C–OOH) . Chemica(–C–OOH) .−1 may refer to vibrations of the present GO skeletal ring [With GO coating, even at low concentrations, several changes in the spectra can be seen in tal ring .−1 can be attributed to the vibrations of benzene rings present in GO [−1 (C–H out of plane for p-hydroxyphenyl units) reduced the intensity [The light band that can be seen at 1560 cmnt in GO . In addintensity .The onset of the degradation step was observed at approximately 64 to 150 °C in both CF and GOCF. This effect may indicate the evaporation of moisture absorbed by the fibers. The main mass degradation step was observed starting at 293 °C for CF and 300 °C for GOCF fibers as can be seen in In the differential thermal analysis (DTA) curves as shown in The degradation ratio of the different fibers, CF and GOCF, in −3 vol% in the composite volume fraction of curaua fiber. Since the thinner GO coating cannot affect the curaua fiber strength.With higher magnification, With higher magnification, one notes that the CF fiber is not very stable under the electron beam, with cracks opening on its surface as can be seen in the Through the EDS analysis in E). Regarding this table, it is important to mention that the values obtained for these properties agree with those reported in the literature [terature ,31.One may infer from the results in olyester . The GOCnterface . TherefoIn the present work, for the first time, ballistic tests were carried out to measure the trauma on the witness clay in MAS target with a second layer epoxy matrix composite reinforced with 30 vol% of curaua fiber both CF and GOCF. In none of the MAS tested, there was complete perforation of the 7.62 mm projectile and the indentation of the clay witness was less than 44 mm, a value considered to be non-lethal to humans by the standard . The resIn The smaller hexagonal ceramic tiles, front MAS layer in Another important participation of the composite plate as MAS second layer is the capture of ceramic fragments resulting from the shattered front ceramic, Capture of fragments, Fibrils separation, also illustrated in Fiber pullout shown in Composite delamination, Fiber breaking, depicted in Matrix rupture exemplified in As a final remark, it is worth reminding that the combination of energy dissipation mechanisms guarantees to a 30 vol% curaua fiber (plain or graphene oxide coated) reinforced epoxy composite as MAS second layer, an acceptable ballistic performance, According to the FTIR analysis, the GO caused changes in the characteristic bands of the CF fibers, suggesting that bonds were formed as well as the appearance of new bands characteristic of the molecular structure of the GO.The thermal degradation of the GOCF fibers was retarded by the action of the GO coating, causing an insulation which contributes to higher temperature resistance, in relation to the CF fibers.Pullout test of untreated curaua fiber (CF) and graphene oxide coated curaua fiber (GOCF) embedded in epoxy matrix revealed a substantial reduction in the GOCF critical length in association with a more than 50 percent higher interfacial shear strength. This behavior is also superior to those of other material fibers.Epoxy composite plates reinforced with 30 vol% of either CF or GOCF, applied as 10 mm thick second layer in a front ceramic multilayered armor system, display a ballistic performance against the threat of 7.62 mm projectile within the backface signature (indentation < 44 mm) required by the standard.This ballistic performance comparable to that of the same thickness Kevlar™ laminate as MAS second layer, was for the first time interpreted as been related to a combination of the following impact energy mechanisms: (i) capture of fragments; (ii) fibrils separation; (iii) fiber pullout; (iv) composite delamination; (v) fiber breaking; and (vi) matrix rupture.The better adherence of GOCF to the epoxy matrix reduces, comparatively, the amount of absorbed energy by mechanisms (ii), (iii), (iv), and (vi). This results in slightly higher ballistic backface signature but a better integrity for the 30 vol% GOCF composites, which is a necessary condition for armor vest using MAS. The plain CF ballistic performance is similar to other natural fibers.It is also ruled out the need of a ductile metal sheet, usually applied as MAS third layer, since the 10 mm thick GOCF composite is enough for the required standard performance.