Drosophila). PALS1 in turn binds to a second scaffolding protein PATJ (PALS1-associated tight junction protein) to form the core Crumbs/PALS1/PATJ complex. While essential roles in epithelial organization have been shown for Crumbs proteins in Drosophila and mammalian systems, the three Caenorhabditis elegans crumbs genes are dispensable for epithelial polarization and development. Here, we investigated the presence and function of PALS1 and PATJ orthologs in C. elegans. We identified MAGU-2 as the C. elegans ortholog of PALS1 and show that MAGU-2 interacts with all three Crumbs proteins and localizes to the apical membrane domain of intestinal epithelial cells in a Crumbs-dependent fashion. Similar to crumbs mutants, magu-2 deletion showed no epithelial polarity defects. We also identified MPZ-1 as a candidate ortholog of PATJ based on the physical interaction with MAGU-2 and sequence similarity with PATJ proteins. However, MPZ-1 is not broadly expressed in epithelial tissues and, therefore, not likely a core component of the C. elegans Crumbs complex. Finally, we show overexpression of the Crumbs proteins EAT-20 or CRB-3 can lead to apical membrane expansion in the intestine. Our results shed light on the composition of the C. elegans Crumbs complex and indicate that the role of Crumbs proteins in promoting apical domain formation is conserved.Crumbs proteins are evolutionarily conserved transmembrane proteins with essential roles in promoting the formation of the apical domain in epithelial cells. The short intracellular tail of Crumbs proteins are known to interact with several proteins, including the scaffolding protein PALS1 (protein associated with LIN7, Stardust in  Cell polarity, the asymmetric distribution of components and functions in a cell, is a fundamental property of animal cells. In epithelial cells, proteins and lipids of the plasma membrane are distributed asymmetrically into an apical domain that faces the external environment or lumen and a basolateral domain contacting neighboring cells and the extracellular matrix. Cell–cell junctions at the boundary of the apical and basolateral domains seal the epithelial sheets to segregate the internal medium from the outside environment and provide mechanical strength to the tissue. The establishment of these different domains relies on mutually antagonistic interactions between evolutionarily conserved polarity complexes. The Scribble group proteins and the Par1 kinase promote basolateral identity, while the apical membrane domain is specified through the combined activities of the Par and Crumbs complexes .Drosophila), and PATJ (PALS1-associated tight junction protein). All three proteins and the physical interactions between them are highly conserved from invertebrates to vertebrates. Crumbs is a transmembrane protein composed of a large extracellular domain, a transmembrane domain, and a short cytoplasmic tail that mediates interactions with other complex members through two protein interaction motifs: a FERM (band 4.1/Ezrin/Radixin/Moesin) domain-binding motif and a C-terminal PDZ (postsynaptic density 95/disks large/zona occludens-1) domain-binding motif (PDZ-binding motif). Crumbs was identified in Drosophila as an essential regulator of polarity in embryonic epithelia, follicular epithelial cells, and photoreceptor cells . Crb1 and Crb2 are similar in size and domain composition to Drosophila Crumbs, while Crb3 lacks most of the extracellular region. Crb1 is predominantly expressed in retinal cells and loss or mutation of Crb1 causes various retinal defects in human and mice, including Leber congenital amaurosis and retinitis pigmentosa   domains, a PDZ domain, a Src homology 3 (SH3) domain, and a guanylate kinase (GUK) domain  domains,, 29. PALst (Sdt) . In mostenotypes , 33, 34.enotypes . Apical enotypes . In miceomplexes , 38.Drosophila Patj and ten in mammalian PATJ). PATJ and PALS1 form an L27 tetramer through the interaction between two units of PALS1-L27N—PATJ-L27 , that consists of an N-terminal L27 domain followed by 13 PDZ domains . PATJ anof MUPP1 , 38.Caenorhabditis elegans is strikingly similar to that of Crumbs proteins in mammalian systems and Drosophila . Reciprocal BLAST using MAGU-2 furthermore identified human PALS1 and Drosophila Sdt as the closest homologs, while BLAST using MAGU-1 identified human MPP7 and Drosophila Metro as the highest scoring hits. MAGU-2 has two predicted isoforms, MAGU-2a of 830 amino acids (aa) and MAGU-2b of 668 aa. A previous analysis of the expression of magu-2 by rtPCR indicated that magu-2b is the predominant isoform (B). The PDZ and SH3 domains of human PALS1 are involved in the interaction with Crumbs, while the GUK domain further enhances the binding. Drosophila Crumbs interacts with Sdt through its intracellular PDZ-binding domain (C. elegans MAGU-2 and CRB-1/EAT-20/CRB-3 (C). Given the best reciprocal blast, the conservation at the amino acid level, and of the domain structure, we conclude that MAGU-2 is the C. elegans ortholog of PALS1.To identify candidate PALS1 homologs, we searched the predicted  and Sdt A. Recipr isoform . Both is isoform B. The PDg domain . Most of20/CRB-3 C. Given C. elegans Crumbs proteins, we performed a yeast two hybrid (Y2H) assay. We fused the intracellular domain of the three Crumbs proteins to the DNA-binding domain of Gal4 and fused the following fragments of MAGU-2 to the activation domain: a full-length fragment, an N-terminal fragment with the PDZ present in the long MAGU-2 isoform (frag. 1), an N-terminal fragment including both PDZ domains but lacking the SH3 domain (frag. 2), an N-terminal fragment that includes both PDZ domains and the SH3 domain (frag. 3), a fragment containing the second PDZ domain and the SH3 domain (frag. 4), a C-terminal fragment containing the SH3 and GUK domains (frag. 5), and a C-terminal fragment consisting of only the GUK domain (frag. 6) (D). The Y2H assay indicated that full length MAGU-2 interacts with each of the three Crumbs proteins (E). Consistent with previous analyses in other organisms  D. The Y2proteins E. Consisrganisms , both thDrosophila Std localize at the apical cortex in epithelial tissues. Thus, if it is a functional ortholog, MAGU-2 would be expected to recapitulate the apical localization of these proteins. To visualize the localization of MAGU-2, we used CRISPR/Cas9 to insert the sequence encoding GFP into the endogenous magu-2 locus. The tag was inserted at the C-terminus such that both isoforms were tagged (A). We first detected MAGU-2::GFP in the intestine during early embryonic development, before apical-basal polarity is fully established, together with DLG-1 at the nascent apical domain (B). During later pharyngeal and intestinal development, MAGU-2 localized to the apical cortex, where it colocalized with the apical protein PAR-6 . Throughout larval development, MAGU-2::GFP localized to the nerve ring and to the apical membrane domain of the pharynx and intestinal cells (E and F). The apical subcellular localization of MAGU-2 in polarized epithelial tissues, which matches the subcellular localization of the Crumbs proteins in these tissues . Animals homozygous for magu-2(mib6) are viable and do not display any obvious developmental defects, suggesting that MAGU-2 activity is dispensable for C. elegans development (B). These findings are consistent with previous observations that the likely magu-2 null alleles ok1059 and gk218 are viable , consistent with both proteins acting in the same pathway.Loss of PALS1/Sdt in mammalian and unctions , 45, 58.unctions , 33, 34.isoforms A. Animalelopment B. These  numbers . Combinin mutant B, consismagu-2 disrupts apical membrane morphology, we examined the localization pattern of the apically enriched intestine-specific actin isoform ACT-5, the apically enriched recycling endosome marker RAB-11, and the apical membrane transporter PEPT-1 in the absence of magu-2. ACT-5 and PEPT-1 localized apically in control animals as well as in magu-2 deletion mutants (C and D). Similarly, RAB-11, which is normally enriched close to the apical lumen in the cytoplasm, maintained the same localization pattern in the absence of MAGU-2 (D). Taken together, these data indicate that, like the crumbs genes, magu-2 is not essential for C. elegans development and suggest that it may not be necessary for apical polarity.To assess in more detail whether loss of  mutants , C and Df MAGU-2 D. Taken Drosophila Sdt depend on Crumbs for their apical localization , indicating that Crumbs is necessary for apical enrichment of MAGU-2. In some systems studied, Crumbs apical localization is also dependent on PALS1 or Sdt  deletion strain. To visualize CRB-3, we used a translational CRB-3::GFP fusion expressed from an integrated extrachromosomal array , indicating that MAGU-2 does not determine CRB-3 localization in C. elegans. Together, these results indicate that the apical recruitment of MAGU-2 depends on Crumbs, while at least the apical localization of CRB-3 is independent of MAGU-2.Mammalian PALS1 and lization , 29, 40.ntestine A, indica1 or Sdt , 59, 60.al array . In contnaltered , B and CC. elegans Crumbs complex contains a PALS1 ortholog, we next investigated the existence of a PATJ ortholog. Drosophila and mammalian PATJ proteins consist of an L27 domain responsible for the interaction with PALS1  (B). BLAST searches with the human and Drosophila PATJ sequences identified the protein MPZ-1 as the most likely C. elegans ortholog. Like mammalian PATJ, MPZ-1 contains ten PDZ domains (B). However, MPZ-1 lacks an easily recognizable L27 domain. Moreover, reciprocal BLAST using MPZ-1 identified two possible human orthologs, PALS1 and MUPP1, while the most similar Drosophila proteins are the basolateral polarity regulators Dlg and Scrib. Therefore, we explored the interaction partners of MAGU-2 in an unbiased fashion, by performing affinity purification of endogenous MAGU-2::GFP from a mixed-stage population followed by mass-spectrometry. The highest-ranking candidate interacting protein was MPZ-1, further suggesting that MPZ-1 is the C. elegans ortholog of PATJ (A).Having established that the th PALS1  followedan PATJ) B. BLAST  domains B. Howeve of PATJ A.Figure B and B and C), we aimed to identify the MAGU-2 domain responsible for the interaction with MPZ-1. We fused the full length MPZ-1 coding sequence to the DNA-binding domain of Gal4 and examined the interaction with the MAGU-2 activation domain fusions described above using Y2H (D). Full length MAGU-2 interacted with MPZ-1, confirming the mass spectrometry result (E). MAGU-2 fragments 2 and 3, which contain the region in which the L27 domain is located in mammalian PALS1 and Drosophila Sdt, also interacted with MPZ-1. This suggests that the region between the first PDZ domain and the SH3 domain of MAGU-2 is necessary for the interaction between MAGU-2 and MPZ-1, despite lacking a recognizable L27 domain. Taken together, these data indicate that the interactions between Crumbs, PALS1, and PATJ are conserved in C. elegans.As the L27 domains through which PATJ and PALS1 interact appear to be absent in both MPZ-1 and MAGU-2 . Consistent with previous reports (B). However, we did not observe expression in epithelial tissues, apart from the spermatheca and excretory canal (C). Thus, while our data indicate that MPZ-1 interacts with MAGU-2, it is likely not a core member of the epithelial Crumbs complex in C. elegans.Previous studies identified several candidate roles for MPZ-1, including in serotonin-stimulated egg-laying through an interaction with the serotonin receptor SER-1 and in DAF-2/insulin signaling in a complex with ARR-1F-18PTEN , 62. AddF-18PTEN , 64. TraF-18PTEN . Howeverisoforms A. Consis reports , MPZ-1 w reports B. Howevery canal C. Thus, crumbs genes demonstrated that the Crumbs complex is not essential in C. elegans . This indicates that overexpression of EAT-20 or CRB-3 results in apical domain expansion. We next investigated the localization of the endogenously GFP-labeled apical determinant PKC-3 (aPKC) upon EAT-20 or CRB-3 overexpression. Consistent with our interpretation that EAT-20 and CRB-3 overexpression induced an increase in apical domain size, we observed apical localization of PKC-3 in the expanded membrane regions (B). Finally, we investigated whether the overexpression phenotype we observed depends on an interaction with MAGU-2. We examined the distribution of YFP::ACT-5 in animals containing the magu-2(mib6) deletion allele and overexpressing EAT-20 or CRB-3. Despite the absence of magu-2, overexpression of EAT-20 or CRB-3 still induced apical domain expansion (C), demonstrating that MAGU-2 is not required for apical membrane expansion.Deletion of all three  elegans . Howeverosophila , have noer elt-2 . To deteer elt-2 A. This i regions B. Finallxpansion C, demonsC. elegans. We identified MAGU-2 as the C. elegans ortholog of mammalian PALS1 and Drosophila Sdt. This conclusion is supported by the sequence conservation, the apical localization of MAGU-2, the dependency of MAGU-2 apical localization on Crumbs proteins, and its interaction with each of the Crumbs orthologs. We also identified MPZ-1 as a candidate ortholog of the Crumbs complex component PATJ, based on sequence conservation and the interaction of MAGU-2 with MPZ-1. However, the more restricted expression pattern of MPZ-1, which is not broadly expressed in epithelia, suggests that it is not a general member of the Crumbs complex but may associate with the Crumbs complex in a tissue-specific manner. Finally, we demonstrate that overexpression of the C. elegans Crumbs proteins EAT-20 or CRB-3 can induce apical membrane expansion in the intestine, though it does so independently of MAGU-2.Here, we characterized the conservation of composition and function of the Crumbs complex in C. elegans. Here, we focused on the homolog of PALS1, MAGU-2, which is a core member of the Crumbs complex in mammalian systems and Drosophila. Deletion of magu-2 did not cause any overt defects in epithelial polarization. A previous study found that MAGU-2 regulates phagocytosis in the epidermis to control the number of synapses of cholinergic motor neurons  and PatJ-PC (Q8NI35) and C. elegans MAGU-2 (C01B7.4b.1), MAGU-1 (Q95XW5-1) and MPZ-1 (G5ECZ8-1). The following sequences were obtained from UniProt (https://itol.embl.de/itol.cgi) (Drosophila PATJ (Q9NB04).Homology searches were performed using BLAST  with the UniProt  and used UniProt  and “Tretol.cgi) . The folSaccharomyces cerevisiae strains Y8930 (MATα) and Y8800 (MATa) using the Te/LiAc transformation method Sequences encoding MAGU-2, CRB-1, EAT-20, CRB-3, and MPZ-1 were PCR amplified from a mixed-stage cDNA library using the primers in C. elegans strains used in this study are derived from the N2 Bristol strain and are listed in Escherichiae coli OP50 bacteria under standard conditions All magu-2::GFP fusion was done by homology-directed repair of CRISPR/Cas9-induced DNA double-strand breaks in an N2 background. The fusion was generated using plasmid-based expression of Cas9 and sgRNAs. The sequence targeted by the sgRNA was 5′ GTGAATACGGAGCCAATGT. The magu-2::GFP repair template was cloned using SapTrap assembly into vector pDD379, and the fusion was repaired using a plasmid-based template with 550 to 600 bp homology arms. A self-excising cassette (SEC) was used for selection (2O and contained 50 ng/μl Peft-3::cas9 (Addgene ID #46168) (The  #46168) , 65 ng/μmagu-2(mib6) deletion was generated by imprecise repair of a CRISPR/Cas9-induced DNA double-strand breaks and selected using the dpy-10 co-CRISPR approach  as previously described (dpy-10 locus (pU6::sgRNA expression vector pJJR50 (Addgene #75026) as previously described (2O and contained 60 ng/ml Peft-3::Cas9 (Addgene #46168), 45 ng/ml each sgRNA plasmid, and 2.5 ng/ml Pmyo-2::mCherry as a coinjection marker . Microinjection of adult N2 hermaphrodites was performed as described above. For selection of edited genomes, injected animals were transferred to individual culture plates, incubated for 3 to 4 days at 20 °C, and 96 nontransgenic F1 animals  from 2 to 3 plates containing high numbers of Dpy and Rol animals were selected and transferred to individual NGM plates. After laying eggs, F1 animals were lysed and genotyped by PCR using two primers flanking the magu-2 open reading frame: 5′ to 3′ left primer CATACGCCCAA TCATCCGCAC, right primer GATGATGATGGTGTCTC TTCTG. Sanger sequencing was used to determine the precise molecular lesion (Macrogen Europe), and the confirmed knockout strain was backcrossed three times with N2.The approach . The fusescribed . The seq10 locus  was clonescribed . The injmpz-1(mib188) allele was generated by homology-directed repair of CRISPR/Cas9-induced DNA double-strand breaks in an N2 background (strain pD1074). The fusion was generated using protein-based expression of Cas9 and crRNAs. Two crRNA were used, targeting 5′ CATTGTTGAGGGATACTGTG and 5′ tactagtctttTCATTGTTG. The GFP repair template was generated by PCR from pJRK86 using the following 5′Sp9-modified primers: 5′ TTCAAATTGCCCGTC CACACAGTATCCCTCAACAAATGAGTAAAGGAGAAG AATT and 5′ tgtgtgagagagggtctacagtactagtctttTCAGTAGAG CTCGTCCATTCCGT. The injection mix contained 30 pmol Streptococcus pyogenes Cas9 3NLS, 90 pmol tracrRNA, 47.5 pmol of each crRNA, 25 ng/μl melted dsDNA, 40 ng/μl of pRF4 (rol-6(su1006)) plasmid, and nuclease-free water to bring the final volume to 20 μl  and equipped with a Yokogawa CSU-X1-M1 confocal head and an Andor iXon DU-885 camera, using 60× or 100× 1.4 NA objectives. All stacks along the z-axis were obtained at 0.25 μm intervals, and all images were analyzed and processed using ImageJ (FIJI) and Adobe Photoshop.Live imaging of Image analysis was done in ImageJ (FIJI). The peak intensity at the apical membrane was measured by drawing a ten pixels wide line scan from the cytoplasm, across the apical membrane and to the lumen. The highest value of the line scan across the apical membrane was selected and the mean background intensity, quantified on a circular region in an area not containing any animals, was subtracted from the intensity measurements. All measurements were taken from regions where opposing apical membranes could be seen clearly as two lines and two intestinal cells per animal were quantified.Animals endogenously expressing GFP-tagged MAGU-2 or control animals expressing an integrated GFP transgene  were groAfter affinity purification, anti-GFP beads were resuspended in 15 μl of 4× Laemmli sample buffer (Biorad), boiled at 99 °C for 10 min, and the supernatants were loaded on 4 to 12% Criterion XT Bis–Tris precast gel (Biorad). The gel was fixed with 40% methanol and 10% acetic acid and then stained for 1 h using colloidal Coomassie dye G-250 . Each lane from the gel was cut and placed in 1.5 ml tubes. Samples were then washed with 250 μl of water, followed by 15 min dehydration in acetonitrile. Proteins were reduced , dehydrated, and alkylated . After two rounds of dehydration, trypsin was added to the samples and incubated overnight at 37 °C. Peptides were extracted with acetonitrile, dried down, and reconstituted in 10% formic acid prior to mass spectrometry analysis.−1. The mass spectrometers were used in a data-dependent mode, which automatically switched between MS and MS/MS. After a survey scan from 375 to 1600 m/z, the ten most abundant peptides were subjected to HCD fragmentation. MS spectra were acquired with a resolution >30,000, whereas MS2 with a resolution >17,500.Samples were analyzed on an Orbitrap Q-Exactive mass spectrometer (Thermo Fisher Scientific) coupled to an Agilent 1290 Infinity LC (Agilent Technologies). Peptides were loaded onto a trap column  with solvent A (0.1% formic acid in water) at a maximum pressure of 800 bar and chromatographically separated over the analytical column  using 90 min linear gradient from 7% to 30% solvent B (0.1% formic acid in acetonitrile) at a flow rate of 150 nl minC. elegans database and Mascot  as the search engine. Carbamidomethylation of cysteines was set as a fixed modification and oxidation of methionine was set as a variable modification. Trypsin was set as cleavage specificity, allowing a maximum of two missed cleavages. Data filtering was performed using a percolator, resulting in 1% false discovery rate. Additional filters were search engine rank 1 and mascot ion score >20. Source of sequence database searched are as follows: Uniprot, release date: October 24, 2017 . Mass tolerance for precursor ions was 50 ppm and mass tolerance for fragment ions was 0.05 Da.Raw data files were converted to mgf files using Proteome Discoverer 1.4 software (Thermo Fisher Scientific). Database search was performed using the Crapome pelt-2::eat-20::mCherry construct was cloned into the pBSK(+) vector using Gibson assembly. The promoter of elt-2, which drives expression in the intestine, was amplified from C. elegans genomic DNA using primers 5′ TAATTTCGAAATGTATGAACTCCA and 5′ CTATAATCTATTT TCTAGTTTCTATTTTATTAGA. A coding fragment of 777 bp including introns was amplified from genomic DNA using primers 5′ ATGACCACGTTTTGTCGAGT and 5′ TCGATTGGATACGGATCGAA. A fragment of 1817 bp without introns was amplified from cDNA using primers 5′ TCACGGGACCAGCCTGCCTA and 5′ GATGTGAGACATCGGCA TCG. A fragment of 749 bp containing the 3′ of eat-20 and 725 bp of 5′ UTR was amplified from genomic DNA using primers 5′ GCCAAGGAGGAGCGGCTGAT and 5′ tagaattttattaattatta. mCherry was amplified from pJJR83 (Addgene #75028) using primers 5′ TCCAAGGGAGAGG AGGACAA and 5′ GTAGAGCTCGTCCATTCCTC. Correct amplification and assembly were confirmed by Sanger sequencing.The pelt-2::crb-3::mCherry construct was cloned into the pMLS257 vector using SapTrap assembly , and 100 fmol of the destination vector (pMLS257). Correct amplification and assembly were confirmed by Sanger sequencing.The assembly . The propmyo-2::TdTomato, and 50 ng/μl of lambda DNA. GFP fluorescence was used to select stable transgenic lines.To generate transgenic lines, young adult hermaphrodites were injected in the germline with the following mix: 65 ng/μl of plasmid of interest, 2.5 ng/μl of via the PRIDE partner repository (The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium  via the pository  with theThis article contains The authors declare that they have no conflicts of interest with the contents of this article.


Rhodopseudomonas palustris, a purple nonsulfur bacterium, is a bacterium with the properties of extraordinary metabolic versatility, carbon source diversity and metabolite diversity. Due to its biodetoxification and biodegradation properties, R. palustris has been traditionally applied in wastewater treatment and bioremediation. R. palustris is rich in various metabolites, contributing to its application in agriculture, aquaculture and livestock breeding as additives. In recent years, R. palustris has been engineered as a microbial cell factory to produce valuable chemicals, especially photofermentation of hydrogen. The outstanding property of R. palustris as a microbial cell factory is its ability to use a diversity of carbon sources. R. palustris is capable of CO2 fixation, contributing to photoautotrophic conversion of CO2 into valuable chemicals. R. palustris can assimilate short-chain organic acids and crude glycerol from industrial and agricultural wastewater. Lignocellulosic biomass hydrolysates can also be degraded by R. palustris. Utilization of these feedstocks can reduce the industry cost and is beneficial for environment. Applications of R. palustris for biopolymers and their building blocks production, and biofuels production are discussed. Afterward, some novel applications in microbial fuel cells, microbial electrosynthesis and photocatalytic synthesis are summarized. The challenges of the application of R. palustris are analyzed, and possible solutions are suggested. Rhodopseudomonas palustris belonging to purple nonsulfur bacterium (PNSB) is widely distributed in nature, mainly in anaerobic water environments with sufficient light, such as lakes, soils, swamps, and the sea   for electricity production   , polysacte (PHB)  and isopte (PHB) , indicatoduction . R. paluis (MES) . Similarynthesis .R. palustris as a microbial cell factory were analyzed. Then, the applications of R. palustris in biopolymers and their building blocks production were discussed. Traditional application of R. palustris in the fields of wastewater treatment, bioremediation, agriculture, aquaculture and livestock breeding were summarized. Application in other fields, including biofuel production, microbial fuel cells, microbial electrosynthesis and photocatalytic synthesis, were also summarized. Finally, the challenges of applications of R. palustris are analyzed, and possible solutions are suggested.In this review, the advantages of R. palustris can utilize various carbon sources for growth, including small molecule organic acids, alcohols, inorganic and aromatic compounds, which are the main components in industrial waste  cycle to participate in cell growth metabolism using thiosulfate as the electron donor  encoding D-lactate dehydrogenase and a gene (RPA1136) encoding lactate permease were predicated in the genome of R. palustris CGA009 , which can replicate in PNSB, was obtained from R. palustris among 400 strains isolated from a natural environment. Then, based on pMG101, Escherichia coli-R. palustris shuttle vectors pMG103 (5.68 kb) and pMG105 (5.68 kb) were constructed, which were stably maintained in R. palustris  was obtained  sources, and co-transformation of pMG103 and pBBR1MCS into R. palustris is promising, which is beneficial for overexpression of several genes in the same strain, broadening the application of R. palustris as a microbial cell factory.Development of genetic engineering tools is necessary for manipulation at the genetic level, such as gene knockout and gene overexpression, which can modify the organism as desired. In alustris . In R. pobtained . The pBBoduction . The ove plasmid . Other palustris . The pMGR. palustris. pJQ200SK is a suicide vector that is widely applied in Gram-negative bacteria, featuring the P15A ori, a gentamicin selection marker and the gene sacB from Bacillus subtilis, encoding sucrose-6-fructosyltransferase, which can catalyze the decomposition of sucrose to high-molecular fructan, which has a lethal effect on Gram-negative bacteria  with T7 promoters were constructed and further utilized for heterogeneous gene expression for sesquiterpenoids synthesis  and adenine base editors (ABEs), all based on CRISPR/Cas9 systems, were also generated  and medium-chain-length PHAs  , have been identified as potential alternatives to traditional plastics, which have been a heavy burden to the environment due to their recalcitrant nature . Dependi C6–C14) . PHAs ar C6–C14) . Althoug C6–C14) . Nonethe C6–C14) . Due to  C6–C14) .2 (carbon source) via photoautotrophy in R. palustris is considered to be sustainable and environmental-friendly. When the electron donor was a poised electrode (photoelectroautotrophy) or a ferrous iron (photoferroautotrophy), it showed the highest PHB electron yield (7.34%) and specific productivity (8.4 × 10−14 mg/cell/h) in R. palustris TIE-1  from p-coumarate  and uppC (RPA4833) were identified to be responsible for unipolar polysaccharide production  and the highest carotenoid productivity   . The ligalustris . Moreovealustris . Among tnditions . TherefoR. palustris has been reported. Due to its antioxidant properties and unique structure, squalene is usually utilized extensively in the pharmaceutical, food, cosmetic and biofuel industries , fusion of two consecutive enzymes (CrtE and HpnD) and overexpression of the dxs gene, squalene yield reached 15.8 mg/g  production. Studies on the production of isoprene in R. palustris has not been reported; however, our group found that the wild type R. palustris can produce isoprene, which was usually produced in plant. Due to its high carotenoids-producing capacity, high isoprene production is promising in R. palustris. Isoprene is produced from precursor DMAPP catalyzed by isoprene synthase , the simplest alicyclic acids, which is degraded to cyclohex-1-enecarboxyl-CoA (CHene-CoA), an intermediate of the benzoate-degrading pathway , a common soil contaminant. An As-redox transformation system exists in R. palustris that can reduce the highly toxic As5+ to As3+ and oxidize As3+ to methylated arsenic (low-toxic)  . The As5 reduced . In the entified . Moreovemulation . In addistrain N . U can balustris . Removalis TN110 .R. palustris has high tolerance and degradation effects toward pesticides and herbicides, which are widely applied in agriculture and forestry. The residual pesticides and herbicides in the agro-ecosystem have caused significant environmental and human health concerns in recent years , one of the most destructive plant viruses. The Rhp-PSP protein with inhibitory activities against TMV in vivo and in vitro was isolated and purified from R. palustris JSC-3b  were also improved by using R. palustris as a water additive  for ammonia production and the hydrogen production is at a low level  relative to the wild type was detected  was obtained , malate (2 g/L), lactate (2.5 g/L), and butyrate (2 g/L), respectively  can also catalyze the synthesis of methane in R. palustris  using petroleum hydrocarbons from oil contaminated sites as the energy source -coated cathode was proven to be the best  coated on its cell surface. An inorganic-biological hybrid system, a CdS-R. palustris hybrid system, was constructed, in which CdS NPs coated on the cell surface can absorb solar energy, release electrons, then participate in various biosynthetic pathways  and a gene knockout vector (pJQ200SK), no other genetic manipulation tools available in R. palustris have been reported. Exploring more genetic tools for R. palustris is necessary. Genetic manipulation tools, such as pRK404 and pIND4, which are available in other PNSBs, may be suitable for R. palustris. In addition, the implementation of some novel gene manipulation technologies, such as CRISPR-Cas and antisense RNA, in R. palustris is promising. Third, most of the research about R. palustris is at the physiological and biochemical levels, and genetic manipulation to enhance its efficiency is rarely reported. For example, for hydrogen production, most of the research has focused on the optimization of culture conditions to improve its production, and only limited research about the genetic manipulation of R. palustris has been reported. However, genetic manipulation could improve the properties of R. palustris significantly. Development of genetic engineering tools would facilitate genetic manipulation of R. palustris to improve its performance.


Firmicutes and Actinobacteria proteomes, yielding over 6,500 confidently predicted fibrillar adhesins. To verify the approach, we investigated predicted fibrillar adhesins that lacked a known adhesive domain. Based on these proteins, we identified 24 sequence clusters representing potential novel members of adhesive domain families. We used AlphaFold to verify that 15 clusters showed structural similarity to known adhesive domains, such as the TED domain. Overall, our study has made a significant contribution to the number of known fibrillar adhesins and has enabled us to identify novel members of adhesive domain families involved in bacterial pathogenesis.Fibrillar adhesins are bacterial cell surface proteins that mediate interactions with the environment, including host cells during colonization or other bacteria during biofilm formation. These proteins are characterized by a stalk that projects the adhesive domain closer to the binding target. Fibrillar adhesins evolve quickly and thus can be difficult to computationally identify, yet they represent an important component for understanding bacterium-host interactions. To detect novel fibrillar adhesins, we developed a random forest prediction approach based on common characteristics we identified for this protein class. We applied this approach to IMPORTANCE Fibrillar adhesins are a class of bacterial cell surface proteins that enable bacteria to interact with their environment. We developed a machine learning approach to identify fibrillar adhesins and applied this classification approach to the Firmicutes and Actinobacteria Reference Proteomes database. This method allowed us to detect a high number of novel fibrillar adhesins and also novel members of adhesive domain families. To confirm our predictions of these potential adhesin protein domains, we predicted their structure using the AlphaFold tool. Fibrillar adhesins are an important class of bacterial surface proteins which are expressed by a wide range of bacterial species to mediate binding interactions. Essential binding targets include different host surface structures, such as extracellular matrix proteins. Pathogenic colonization and infection can occur as a consequence of the binding interactions to host cells . Single Fibrillar adhesins are a recently defined class of proteins that led to a domain-based characterization and identification of these proteins across a wide range of bacterial species , 7. Key Firmicutes and Actinobacteria UniProt Reference Proteomes database and verify the approach by predicting the structure of Firmicutes FA-like proteins lacking a known adhesive domain with AlphaFold  proteins across all bacterial species based on profile hidden Markov model (HMM) searches . The limlphaFold . Our appThe aim of this study is the extension of the identification of fibrillar adhesins compared to the domain-based approach described in our earlier study . To achiFirmicutes and Actinobacteria phyla in this study. Fibrillar adhesins are best studied in Firmicutes, and the cell surface composition and FA-like protein architecture of the Actinobacteria resemble those of the Firmicutes  have at least one adhesive and one stalk domain, whereas less than 0.1% of the proteins in the negative training set possess a known adhesive or stalk domain. Hence, the adhesive and stalk domains are the strongest identification features for this protein class . To incr8% have aFibrillar adhesins are attached to the bacterial cell surface. Known anchor domains or sortase motifs were found in 846 out of 1,666 proteins of the positive training set and were used as another identification feature.FA-like proteins are among the longest proteins in the proteome; thus, the protein length turned out to be one of the strongest prediction features . Their lTo characterize the protein sequence of FA-like proteins, the amount of charged, as well as hydrophobic, amino acids per protein was selected as an additional feature. The protein sequences of the positive training data tend to have a slightly lower fraction of charged amino acids and tend to have a lower fraction of hydrophobic amino acids than the negative training data set.Finally, we selected features related to the sequence composition. We calculated the fraction of each amino acid per sequence as well as the relative entropy describing the sequence composition bias. We observed that the relative entropy tends to be slightly higher in the positive training set and that threonine is 1.8-fold increased and leucine is 1.5-fold decreased in the positive training set compared to the negative training set .We implemented the selected features in a random forest classification approach and analyzed the feature importance in the classification prediction based on the training data . The adhAn important challenge of this work is to determine the random forest score threshold that will reliably identify novel FA-like proteins that potentially lack known stalk or adhesive domains.Firmicutes and Actinobacteria UniProt reference proteomes, 45,444 FA-like proteins with a prediction score above 0.5 were identified, 24,197 proteins in Firmicutes and 21,247 proteins in Actinobacteria , we predicted their subcellular localizations using PSORTb (version 3) . For neaell wall . For mosell wall . ConsequEven though most of the proteins (>75%) predicted with a score of 1.0 with known stalk domains have an adhesive domain, over 90% of the predicted FA-like proteins above a prediction score of 0.5 with known stalk domains have no known adhesive domain  and 3. GFirmicutes . We carried out two analyses, (i) to search for overlapping known Pfam domains, using the highly sensitive iterative Jackhmmer search, and (ii) to predict the structure of the sequence using AlphaFold , 17. UsiThe Jackhmmer search using the putative adhesive region indicated 8 out of the 24 sequence clusters  to be similar to known adhesive domain sequences . These s(i) Cluster 2. The predicted structure of cluster 2 representative sequence (UniProtKB accession no. K8EVB1) shows that it contains two distinct domains . For the C-terminal end of the C-terminal domain of cluster 2, the Jackhmmer search indicates an overlap with the Collagen_bind domain (Pfam ID PF05737). The second domain structure yields, with the DALI search, the Streptococcus gordonii adhesin Sgo0707, where the structure superposes to the Sgo0707_N2 domain . The subsequent DALI hits are the SdrG_C_C adhesive domain  . The SdrG_C_C domain is also often found associated with the Big_8 domain in known adhesins and is likely to be homologous to the Collagen_bind domain. Cluster group 2 includes the Enterococcus faecalis protein with the gene name ef2505 or fss2, which was described to bind to fibrinogen and play an important role in the adherence and virulence of E. faecalis  Cluster 6. For cluster 6, AlphaFold predicted a structure composed of two domains (5CF3:A), and for the C-terminal domain, a Collagen_bind domain as the best match (PDB ID 2Z1P:A) , thereby confirming the Jackhmmer search results. The Big_8 domain functions together with the Collagen_bind domain as a supradomain, enabling the binding to collagen by the collagen hug binding mechanism ( domains . The DALechanism .(iii) Cluster 15. Cluster group 15 includes the Listeria monocytogenes InternalinJ (UniProtKB accession no. Q8Y3L4), for which the crystal structure of the adhesive domain exists (PDB 3BZ5:A) ( 3BZ5:A) , which w(iv) Cluster 8. The Jackhmmer search, as well as the DALI search, with the AlphaFold prediction indicate cluster 8 being a class II TED (Pfam ID PF08341) adhesive domain (PDB ID 6FX6:A) , as well as an E. faecalis protein (UniProtKB accession no. Q831Z5) encoded by the virulence-associated ef2347 gene ( 6FX6:A) , 25. The 6FX6:A) . Cluster347 gene .(v) Cluster 17. The Jackhmmer search indicates cluster 17 to also be distantly related to the TED adhesive domain (6FWV) (e domain . The DAL(vi) Cluster 19. Again, a TED domain was indicated by the Jackhmmer search for cluster 19 and supported by the DALI results (PDB ID 6FX6:A) ( 6FX6:A) . An exis(vii) Cluster 21. The predicted structure of cluster 21 showed two distinct domains (3KPT:A), which only aligns with the beta-strands of the domain. Interestingly, the N-terminal TED-like domain is predicted to interact with the C-terminal domain.(viii) Cluster 24. The Jackhmmer search, as well as the DALI results, indicates a TED domain for cluster 24 (PDB ID 6FWY:B). The existing beta-stranded insertion clearly characterizes this TED domain as a class II TED domain  (The best DALI hit for cluster group 4 was a GramPos_pilinBB domain of the RrgB pilus backbone (PDB ID Clostridium perfringens pilin protein (PDB ID 5XCB:A) with the GramPos_pilinBB domain (Pfam ID PF16569) .The Jackhmmer search for cluster group 5 showed an overlap with the MBG stalk domain at the C-terminus of the sequence, which was trimmed off, leaving a significant N-terminal sequence region for which the structure was predicted. The top DALI matches are related to surface adhesins, with the best match being a 1AMX:A). The structure surfaces seem to provide a groove on the beta-sheets, indicating a potential collagen binding site (The Evolutionary Classification Of protein Domains (ECOD) databases classify the GramPos_pilinBB domain under the topology named “Common fold of diphtheria toxin/transcription factors/cytochrome f” . This caing site . Howevering site . The simLactobacillus reuteri strain 100-23C (PDB ID 5NY0:A) , being described to bind to epithelial cells and pectic acids and play a role in biofilm formation , which was, so far, only found associated with the Bact_lectin adhesive domain (Pfam ID PF18483) in S. epidermidis and S. aureus SasG homologues  , where the representative protein sequence (UniProtKB accession no. A0A0F7RLJ7) is identical to a Bacillus anthracis protein (UniProtKB accession no. A0A384LNE7) with the gene name BA_0871 or BASH2_04951, which was described to be collagen binding and to be linked to bacterial pathogenicity  , which superposes with the N-terminal alpha helices of the structure model (S. aureus SdrD adhesive protein (PDB ID 4JDZ:A), where the structure model superposes with the SdrD_B stalk domain (Pfam ID PF17210). Cluster 3 includes one Streptococcus merionis protein (UniProtKB accession no. A0A239SMH4), which is encoded by the bca gene. The bca gene has been shown to be involved in the initial stage of group B Streptococcus infection , followed by the best bacterial match being the N-termini of the S. gordonii adhesin Sgo0707 (PDB ID 4IGB:B)  encoded by the ef3314 gene, which was described to contribute to the virulence properties of this pathogen   and, for the C-terminal domain, a similarity to the BcpA major pilin subunit (PDB ID 3RKP:A).The Jackhmmer search for cluster 11 resulted in the known DUF11 (Pfam ID PF01345) stalk domains. The predicted structure shows two distinct domains . The DAL5l5G:D) (6VXK:D), where the cluster aligns to the two TIG domains in the protein, whereby only the N-terminal subdomain superposes well . But separately, both subdomains of the N-terminal part superpose reliably to a TIG domain, suggesting the N-terminal part to be related to a combination of two TIG domains, which might have developed further. A groove on the surface of the structure model indicates that the N-terminal part might have developed a binding function  . The middle domain resembles a stalk-like structure in Intimin_C (PDB ID 1F00:I), and the best DALI hit for the C-terminal domain was the CfA/I fimbrial subunit A (PDB ID 6K73:B).The structure model for cluster 20 presents three domains . The Jac4U7K:G) and Big_2 (PDB ID 4HU8:C), respectively (1YEW:E) closely followed by the I-set immunoglobulin-like stalk domain (PDB ID 5AEA:A).The sequence of cluster 22 also indicated a Big_2 stalk domain. The predicted structure again represents three domains, of which the N-terminal and C-terminal domains are most similar to the stalk domains PKD_4  and, for cluster 18, a putative immunoglobulin protease (PDB ID 3N6Z:A), suggesting potential catalytic functions (The Jackhmmer search indicated a Beta_helix (Pfam ID PF13229) for cluster 7 and a Peptidase_M26_N (Pfam ID PF05342) domain for cluster 18. The structure models of both domains resemble carbohydrate binding pectate lyase adhesive domains. But the top DALI hit for cluster 7 is a lacto-1IUB), suggesting cluster 16 as having adhesion function (2Z2O:B), again suggesting catalytic function (Jackhmmer indicated a BNR_4 (Pfam ID PF15892) domain for cluster 16, and the top DALI hit for this cluster is a human integrin alpha-IIb protein, which binds, among others, to fibrinogen. The InterPro database has a Fucose_binding_lectin domain annotated  (The best DALI hit for cluster 23 was the P_proprotein domain (Pfam ID PF01483) of a protease, which is common to be located downstream of a catalytic domain (PDB ID 3HJR:A) .The results of the above-described clusters suggest the clusters play a catalytic role, not ruling out binding abilities. Given that catalytic domains often also have adhesive function to bind to their substrate, it is challenging to differentiate between catalytic and adhesive domains and also between fibrillar adhesins and, as we call them, “fibrillar enzymes.” Fibrillar enzymes are also composed of repeating domains but have an enzymatic-related domain instead of an explicit adhesive domain . NeverthFirmicutes and Actinobacteria UniProt Reference Proteomes database, yielding over 6,500 confidently predicted FA-like proteins.Novel pathogens are emerging constantly with uncharacterized host-cell interaction mechanisms. Homologous virulence-associated proteins with known adhesive domains are the first step toward an understanding of the pathogenicity of these bacteria. But adhesive domains evolve quickly and are highly variable. Hence, detection mechanisms independent of known adhesive domains are important. In this study, we developed a random forest-based discovery approach to detect FA-like proteins. We applied the approach to the Firmicutes and Actinobacteria UniProt Reference Proteomes database led to over 6,500 confidently detected FA-like proteins. This indicates that more than 5,000 of them were missed by the domain-based discovery approach detected in our previous study .We selected, as positive training data, the FA-like proteins of us study . AdditioTo search in the protein sequences for known adhesive, stalk, and anchor domains, the collection of Pfam domain HMMs from our previous study was used . AdditioTo identify highly similar tandem sequence repeats that may represent potential unknown stalk domains, we applied the T-REKS software to the sequences, using, as parameters, a minimum of 70% sequence identity, 50 residues as minimum length of the repeat region, and 5 residues as minimum seed length .Disordered regions were predicted using IUPred (IUPred2a) with the IUPred2-type “long” for predicting long disordered regions . Each reThe proportion of charged or hydrophobic amino acids per protein sequence was calculated using, as charged amino acids, glutamic acid (E), aspartic acid (D), lysine (K), and arginine (R) and, as hydrophobic amino acids, alanine (A), isoleucine (I), leucine (L), methionine (M), phenylalanine (F), tryptophan (W), tyrosine (Y), and valine (V).The residue length was counted per the complete UniProt protein sequence.S). Here, we quantify the difference between the observed frequency (P) per amino acid (i) compared to equally frequent amino acids, being 0.05 for 20 amino acids.The proportion for each amino acid per protein sequence was calculated, and to evaluate the amino acid composition bias, the relative entropy (Kullback-Leibler [KL] divergence) was calculated per protein sequence .Firmicutes and Actinobacteria proteins, we first gathered available sequences. The UniProt proteome identifier for all Firmicutes and Actinobacteria reference proteomes was searched for on the UniProt website (release 2020_04). We collected the relevant sequences for these identifiers by searching in the knowledgebase under the bacterial reference proteomes (release 2020_03) for the identifier.To apply our machine learning method against known Firmicutes and Actinobacteria reference protein sequences and applied the trained random forest classification approach to score each protein.As described in the subsection “Identification features calculation and random forest classification,” we calculated the identification features for the We further analyzed the predicted FA-like proteins by differentiating the prediction scores. The subcellular localizations of the predicted FA-like proteins were predicted using singularity (version 3.5.3) to run the PSORTb (version 3) Docker image (psortb_commandline_1.0.2.sif).To find distantly related adhesive domains, a profile HMM search with the known adhesive domains was conducted using an E-value threshold of 1.0.Using profile HMM-search (version 3.1b2) with the GA threshold option, the Pfam database (version 33.1) was run against the sequences of the predicted FA-like proteins.Firmicutes and Actinobacteria is mostly found at the N-terminus  to find domain families related to the sequence clusters  (The structure for each representative sequence was predicted with AlphaFold2 using the Google colab repository provided by DeepMind (d.ipynb) . Based oTo assess the quality of the models, AlphaFold stores the pLDDT confidence in the B-factor field of the output PDB files, which were used to color the structure models by quality using Chimera . To findWe created an HMM from the sequences per cluster based on the detected domains using hmmbuild . With thFirmicutes and Actinobacteria reference proteomes can be found in an institutional repository of the University of Cambridge (https://www.repository.cam.ac.uk/handle/1810/335004) (https://github.com/VivianMonzon/FAL_prediction), which includes the training data set and the code to run the random forest-based FA-like protein prediction on a sequence of interest, as well as a colab notebook (https://colab.research.google.com/github/VivianMonzon/FAL_prediction/blob/main/Colab/ML_FA_prediction.ipynb).The AlphaFold structure model, as well as the random forest prediction results, for the /335004) . We prov


Due to the rise in the number of people suffering from diet-related noncommunicable diseases, major scientific studies have recently been focused on the development of functional foods that are rich sources of resistant starch and bioactive compounds with health-promoting properties. The nutritional composition, in vitro starch digestibility, and antioxidant properties of composite flour derived from wheat and mature, unripe pawpaw fruit flour are all discussed in this study. The proximate composition, functional and pasting properties, in vitro starch digestibility, antioxidant activities and storage stability of the composite flours were determined. When compared to 100% wheat flour, the crude fiber, ash, water absorption capacity, swelling capacity, and bulk density of the composite flours increased by 40.5–63.3%, 209.7–318%, 2–109%, 3–66%, and 28–162%, respectively. Increased addition of mature, unripe pawpaw fruit flour to wheat flour resulted in a rise in the composite flour’s TPC, ABTS, and ORAC values. Comparing the composite flour made with 50% mature, unripe pawpaw fruit flour to 100% wheat flour, the resistant starch and slowly digested starch rose by 2836% and 1321%, respectively. Additionally, compared to 100% wheat flour, the composite flours also demonstrated decreased fat acidity. It can be argued that the composite flour is a good source of resistant starch and bioactive ingredients that can be used in a variety of functional food products. Diet-related noncommunicable diseases like type II diabetes, cancer, and cardiovascular disease are a major problem worldwide. Estimates indicate that 23.3 million additional people could die from cardiovascular disease by 2030, up from the 17.5 million who did so in 2012 . It is wCarica papaya) is a great way to get more dietary fibre and reduce constipation in people. Papaya’s fibre content can aid in decreasing high blood cholesterol levels [Consuming the entire pawpaw fruit , which is imported into Africa [Triticum aestivum L.), which is also used to make bread, scones, other confections, noodles, and pasta [One of the most significant staple food crops for many nations is wheat  was obtained from Teaching and Agricultural Farm OAU (Obafemi Awolowo University), Ile-Ife, Nigeria, while the wheat flour was purchased at the central market in Obafemi Awolowo University.The mature, unripe pawpaw fruit was washed and peeled manually using a knife. The peeled mature, unripe pawpaw fruit was deseeded, cut into smaller pieces and dried at 50 °C for 72 h using a forced air oven. The dried pieces were milled into flour using a hammer mill  and sieved with a 500-micron sieve. The flour was packaged in ziplock bags and stored at 4 °C for further analysis.The wheat flour and mature, unripe pawpaw fruit flour were mixed at different ratios. The 100% wheat flour serves as the control sample (A). The 90% wheat flour to 10% mature, unripe pawpaw fruit flour serves as sample B, while 80% wheat flour to 20% mature, unripe pawpaw fruit flour is sample C. Samples D, E, and F, respectively, were made with a ratio of 70% wheat flour to 30% mature, unripe pawpaw fruit flour, 60% wheat flour to 40% mature, unripe pawpaw fruit flour, and 50% wheat flour to 50% mature, unripe pawpaw fruit flour. According to our preliminary study, using mature, unripe pawpaw fruit flour more than 50% resulted in cookies that the panelists found to be quite unappealing and were scored very low in terms of overall acceptability; therefore, we chose to stop at 50%. This may be due to a reduction in glutenin and gliadin protein and a higher amount of starch and fibre. The flours were homogenized properly and packed in ziplock bags and stored in a refrigerator (4 °C) for further analyses.Using the AOAC method , the proW1) inside the centrifuge tube. The sample was vortexed for 10 min, followed by another 10 min of rest. The suspension was centrifuged at 4100× g for 15 min (25 °C). The residue-filled tube was weighed after the supernatant was decanted (W2). The formula below was used to calculate the WAC.The Bamidele et al.’s  modifiedg for 15 min at 25 °C. The centrifuge tube’s only remaining portion was dried in a hot air oven (50 °C) for 30 min before being weighed after the supernatant was removed. The bulk density was calculated by weighing precisely 10 g of the composite flour sample into a 25 mL graduated cylinder and gently tapping the cylinder on the lab bench until no change in volume was noticed. The sample’s final volume was measured, and the difference between the two was computed to obtain the bulk density, which was then expressed in g/mL. The sample’s water solubility index was calculated using the proportion of dry particles that was recovered from the supernatant after drying overnight in an oven at 100 °C.The swelling capacity of the composite flour sample was evaluated using a modified method of Bamidele et al. . Exactlyg for 10 min, the supernatant was separated, and the residue was rinsed four times each with 10 mL MeOH/HCl and centrifuged as above. The supernatants were pooled together and stored at 5 °C in the dark until analysed.For the free phenolics extraction, 1 g of each flour sample was extracted with 10 mL of MeOH/HCl (85:15) by magnetic stirring for 2 h. The extract was then centrifuged using a Rotanta 460R Hettiech  at 2000× 2CO3 were added to each tube. The reactants were incubated in the dark at room temperature for 2 h. Afterwards, 200 µL of the reaction mixture were transferred from the assay tube to a clear 96-well microplate and absorbance was read at 750 nm. The catechin standard curve was used to calculate the total phenolic content, which was expressed as milligram catechin equivalent per gram (mg CE/g) of flour on a dry basis.A 100 µL aliquot of each extract from composite flour , catechin standard or blank was separately added to a 2 mL Eppendorf microtube in duplicate. To each microtube, 200 µL of 10% Folin–Ciocalteu (F–C) reagent was added, and the mixture was thoroughly vortexed. Subsequently, 800 µL of 700 mM Na+ radical scavenging capacity of the aliquot of each extract from the composite flour  was measured using the method of Apea-Bah et al. [+ stock solution of 0.01 M with 58 mL of PBS (pH 6.9). The mixture was left in the dark for 12–16 h. The mixture of the aliquot extracted from the composite flour and the working solution was left in the dark for another 30 min before the absorbance was read at 750 nm. Trolox solution served as the standard and results were reported as μmol TE/g db.The ABTSh et al. . The worThe ORAC of the composite flour sample was measured based on the modified method of Ou et al. . The fluA Rapid Visco Analyser (RVA) series 4  was used for the pasting profile of the composite flour. The sample was placed into the canister weighing around 3 g, and twenty-five (25) mL of distilled water was then added. A paddle was placed inside the canister , then inserted into the RVA machine. The measurement cycle was initiated by pressing the motor tower of the instrument and a 14 min profile was applied. The time–temperature regime used was idle at 50 °C for 1 min, heated from 50 °C to 91 °C in 4 min, then held at 91 °C for 3 min. The sample was subsequently cooled to 50 °C for a 4 min period, followed by a period of 2 min where the temperature was controlled at 50 °C . All meag of porcine pancreatin in 80.0 mL of water for 10 min at 1500 g to create enzyme solution II. Just prior to use, water (4.0 mL), enzyme solution I (6.0 mL), and enzyme solution II (6.0 mL) were combined to create enzyme III (54.0 mL). A composite flour sample  was put in a polypropylene centrifuge tube (30.0 mL), together with enzyme solution III (5.0 mL) and sodium acetate buffer (pH 5.2). The tube was shaken in a water bath at 37 °C (90 strokes per minute). Following 20 min, 0.5 mL of the digest was added to 20.0 mL of 66% ethanol, which was then combined and centrifuged. The amount of glucose in the supernatant was measured using glucose oxidase, and RDS was calculated by multiplying the amount of glucose (in mg) released by 0.9 and dividing it by 200 mg. The amount of glucose released after 120 min of digestion is known as resistant starch, whereas the amount released between 20 and 120 min is known as slowly digested starch (SDS), and the amount released after 20 min is known as quickly digestible starch (RDS). The following formulas were used to determine how much glucose was produced in 120 min.FG = glucose content after 0 min of digestion, G20 = glucose content after 20 min of digestion, G120 = glucose after 120 min of digestion, TS = total content starch.The in vitro starch digestibility of the composite flour was determined by a modification of the procedure of Englyst et al. . Enzyme Lipids were extracted from flour samples using petroleum ether . Fat acidity was analysed by acid-base titration according to the AACC Method 02-02 A . All parAll data obtained were subjected to analysis of variance (ANOVA) using the Statistical Package for Social Science . Significant means were separated using Duncan’s multiple comparison tests at 5% level of probability.p > 0.05) in moisture content of all the samples. The proportion of the mature, unripe pawpaw fruit flour (MUPFF), which ranges from 10 to 50%, caused the crude protein content of the composite flours to drop by roughly 16 to 24%. The highest value (12.68%) was in the control sample, which contained only wheat flour, and was followed by composite flour containing 10% MUPF. For the composite flour with 50% MUPF, the lowest crude protein value (9.12%) was found. The pattern for crude fat was the same as for crude protein. The control sample had the highest crude fat value (3.11%), followed by the sample with 10% MUPF (3.01). The least amount of crude fat (1.62%) was found in the composite flour that contained 50% MUPFF. As the proportion of MUPFF added to wheat flour rose from 10% to 50%, the crude fiber and ash content of the composite flours significantly increased (p < 0.05). The composite flour containing 50% MUPF had the highest crude fiber value (8.67%), whereas the control sample had the lowest (5.31%). The control sample also had the least amount of ash (0.72%), which was followed by the composite flour containing 10% MUPFF (2.23%). The highest value, 3.01%, was found in the composite flour containing 50% MUPFF. The carbohydrate content of the control sample and the composite flour with 20, 30, 40, and 50% MUPFF did not differ significantly (p < 0.05). The least amount of carbohydrate (67.94%) was found in the composite flour containing 10% MUPFF.The proximate composition of 100% wheat flour and the composite flours made from wheat and mature, unripe pawpaw fruit is shown in The addition of MUPFF to wheat flour brought about variations in the flour samples’ proximate composition. For instance, lower levels of crude protein and crude fat in MUPFF compared to wheat flour led to a reduction in the levels of crude protein and fat in the composite flours compared to 100% wheat flour, while higher levels of crude fiber and ash in the composite flours compared to 100% wheat flour can be attributed to MUPFF’s high levels of crude fiber and ash, as previously reported . This shp < 0.05) by approximately 33–109% as the levels of the substitution of the WF with MUPFF in the composite flour increased from 10 to 50%, indicating that the inclusion of MUPFF was able to increase the ability of the flour to absorb water. This may be attributed to the presence of more hydrophilic constituents such as polysaccharides or higher starch damage in the MUPFF compared to the 100% WF. As indicated in The functional properties of the composite flour made from wheat flour and unripe pawpaw fruit flour, as determined by water absorption capacity, swelling capacity, bulk density, and water solubility index, are displayed in Swelling capacity has been identified as one of the criteria for a high-quality product. Important characteristics that eventually influence sample consistency include swelling and water absorption capabilities, which depend on the compositional structure of the sample. When preparing food, flours with high water absorption and swelling capacities hold a lot of water. The swelling capacity of the flour samples followed a similar pattern with water absorption capacity, as the value ranged from 127.74 to 173.22 for 100% WF and 50 WF + 50 MUPFF, respectively. The value increased by 3–36% as the proportion of the MUPFF in the composite flour increased from 10 to 50%, indicating that the incorporation of the MUPFF significantly affects the swelling capacity of the flour mixture.The relatively high fibre content and chemical makeup of the MUPFF, which have the capability to absorb water molecules, may be responsible for the composite flour’s increased swelling capacity when compared to 100% WF . Food quThe incorporation of MUPFF into WF also enhanced the bulk density of the composite flour as the value increased from 1.53 ± 0.5 (100% WF) to 4.01 ± 0.6 (50 WF + 50 MUPFF), indicating that the value increased by approximately 28–162% as the proportion of the MUPFF in the composite flour increased from 10 to 50%. Bulk density is a measure of a product’s porosity that affects packaging design and may be used to choose the right kind of material for wet processing in the food industry, as well as to determine how to handle materials. High bulk density is a good physical property to consider when assessing the mixing quality of a particular matter .p < 0.05) fell from 2.93 ± 0.2 (100% WF) to 1.03 ± 0.2 (50 WF + 50 MUPFF) when the percentage of the MUPFF increased from 10 to 50%. The water solubility index indicates the amount of free polysaccharide or polysaccharide liberated from the granule when too much water is added to the flour and thus shows the degree of starch breakdown [The water solubility index, in contrast to other functional parameters found, significantly  compared to the 100% WF. The results clearly showed that the TPC, and radical scavenging activities of the composite flours, increased significantly as the proportion of the MUPFF increased from 10 to 50%, indicating that incorporation of MUPFF into WF may enhance its health-promoting properties. These findings highlight the significance of incorporating MUPFF into WF in food preparation. Since the flour sample with the highest TPC also had the highest radical scavenging activity, the data further suggested that the phenolic components in the flour samples are what give it its radical scavenging properties.p < 0.05). Peak viscosity, which is the highest viscosity that develops during or shortly after heating the flour samples and a measure of the starch’s capacity to bind water, ranged from 120.46 ± 1.5 to 202.41 ± 1.6, with 100% WF having the lowest value and the composite flour made up of 50% WF and 50% MUPFF having the highest value. Peak viscosity measurement is essential for determining the cooking and baking qualities of flour. The results clearly indicated that peak viscosity increased significantly (p < 0.05) by approximately 18 to 68% as the proportion of MUPFF in the composite flour increased from 10 to 50%, suggesting that the composite flours had higher water binding potential compared to 100% WF. Since proteins and fats are known to reduce peak viscosity through their interaction with starch, the higher peak viscosity seen in the composite flours may be explained by the lower crude fat and protein contents in MUPFF compared to WF. Considering that composite flours have a high peak viscosity, the results indicated that they would yield stiff dough products with good textural quality [As demonstrated in  quality . This isThe trough viscosity is the point during either a heating or cooling process where the viscosity is at its lowest. It measures how well the paste will hold up to disintegration during cooling. The value ranged from 76.46 ± 0.5 (100% WF) to 92.21 ± 0.8 (50% WF + 50% MUPFF). The tendency of the composite flours to disintegrate during cooking is indicated by the much higher trough viscosity seen in the composite flours compared to 100% WF. When compared to 100% WF, the breakdown viscosity of the composite flour was significantly higher (by about 44 to 151%), indicating that 100% WF will be able to withstand heat and shear stress better than the composite flours. This is because the breakdown viscosity is a measure of the stability of the starch and an index of how well the paste will withstand heat and shear stress during cooking. Adebowale et al.  found thp < 0.05) higher setback viscosity values (by 107–399%) than the 100% WF, suggesting that the end products made from these flour samples will be less prone to retrogradation and staling. The tendency for retrogradation and staling is less common in flour samples with a higher setback viscosity [Final viscosity, which reflects a flour’s capacity to transform into a sticky paste after cooking and cooling, is frequently used to describe a starch-based flour’s quality. Additionally, it provides a measurement of the paste’s resistance to shear force during stirring. The final viscosity values ranged from 112.51 ±1.6 to 272.43 ± 1.6, with 100% WF having the lowest value and the 50:50 flour mixture having the highest value, demonstrating that the addition of MUPFF to WF improved the composite flour’s capacity to create a thick paste after heating and cooling. The composite flours showed considerably (iscosity . Peak tiThe in vitro starch digestibility of the flour samples is shown in The increase in the RS of the composite flour may be attributed to a higher amount of crude fibre in the MUPFF  and the The composite flours made from wheat and mature, unripe pawpaw fruit flour are relatively stable for nine weeks of storage in addition to having high-resistant starch, antioxidant activity, and good pasting qualities. This makes the composite flours a healthy raw material for the food industry when producing confectionaries and other functional foods. This study highlights the significance of compositing wheat flour with mature, unripe pawpaw fruit. While the composite flour’s levels of crude protein and crude fat dropped, ash, resistant starch, and antioxidant activity significantly increased. The composite flour also offers enhanced storage stability and superior pasting properties. It can be concluded that adding mature, unripe pawpaw fruit flour to wheat flour may aid in the development of a variety of functional foods, especially for those living with diabetes.


Staphylococcus epidermidis utilizes a multidomain surface adhesin protein to bind host componentsand adhere to tissues. While it is known that the interaction betweenthe SdrG receptor and its fibrinopeptide target (FgB) is exceptionallymechanostable (∼2 nN), the influence of downstream B domains(B1 and B2) is unclear. Here, we studied the mechanical relationshipsbetween folded B domains and the SdrG receptor bound to FgB. We usedprotein engineering, single-molecule force spectroscopy (SMFS) withan atomic force microscope (AFM), and Monte Carlo simulations to understandhow the mechanical properties of folded sacrificial domains, in general,can be optimally tuned to match the stability of a receptor–ligandcomplex. Analogous to macroscopic suspension systems, sacrificialshock absorber domains should neither be too weak nor too strong tooptimally dissipate mechanical energy. We built artificial molecularshock absorber systems based on the nanobody (VHH) scaffold and studiedthe competition between domain unfolding and receptor unbinding. Wequantitatively determined the optimal stability of shock absorbersthat maximizes work dissipation on average for a given receptor andfound that natural sacrificial domains from pathogenic S. epidermidis and Clostridium perfringens adhesins exhibit stabilities at or near this optimum within a specificrange of loading rates. These findings demonstrate how tuning thestability of sacrificial domains in adhesive polyproteins can be usedto maximize mechanical work dissipation and serve as an adhesion strategyby bacteria.The opportunisticpathogen  Staphylococcus epidermidis is acommon commensal bacterium of the skin and nasal microbiome that colonizesimplanted medical devices and causes infection. Although S. epidermidis possesses a smaller number of virulencefactors than Staphylococcus aureus,it maintains a number of cell-wall anchored adhesins that promotebiofilm formation and host infection by binding to extracellular matrixand blood proteins including collagen, fibronectin, and fibrinogen.2 These blood and matrix components coat implanted medical devicesas part of the foreign body response and serve as potential reservoirsfor infection. This has led to a need for understanding bacterialadhesion mechanisms in an effort to combat antibiotic-resistant infections.S. epidermidis, SdrG is a member of the microbialsurface components recognizing adhesive matrix molecules (MSCRAMMs)family. SdrG is a multidomain polyprotein that has received significantinterest due to the ultrastable force-activated interaction it formswith the N-terminal fibrinopeptide of the fibrinogen Bβ-chain(FgB)4 that requires >2 nN to dissociate at105 pN/s but maintains moderate thermodynamic affinitywith KD = ∼400 nM.5 Adjacent to the SdrG N2-N3 receptor domains (referred toas theA region) are two globular B domains (B1 and B2) with ultrastablemechanical properties typical of Gram-positive adhesins,7 requiring >2 nN of tension to unfold at 105 pN/s.8 These mechanostable adhesin proteins are knownto be critical for maintaining tissue adhesion under flow and contributingto biofilm formation on medical device surfaces.9Among the various cell-wall-anchored adhesins of S. epidermidis native receptor, comprising SdrG (N2-N3) fused with B1 and B2 domains.Specifically, we considered the amount of mechanical work that isrequired to unfold and stretch these polyproteins under constant speedand constant loading rate protocols. When force is applied to anchoredB domains using the SdrG:FgB interaction as a pulling anchor , the observed unfolding forcedistribution of the B domains is biased toward lower forces. Thisarises because the SdrG:FgB interaction used to apply tension acrossthe B domains has finite stability and frequently breaks prior toB domain unfolding. The questions that arise from this scenario are:(1) Given this biasing effect, how can we measure the true mechanicalunfolding parameters of B domains? (2) How does the stability of Bdomains influence the amount of mechanical work required to stretchthe polyprotein through the SdrG:FgB interaction? (3) Is there optimaldomain stability that maximizes mechanical work dissipation upon unfoldingand stretching the sacrificial domains (on average), and how doesthat optimum compare with native B domain mechanics?Here, we studied the loading response of engineeredpolyproteinsmimicking those found in the 12 Protein unfolding releases hidden biopolymer contourlength that requires the input of mechanical work to extend, and thiseffect can act as a shock dissipator in biomaterials under tension in diverse systems including bone,18 muscle,20 fibrin,22 collagen,23 as well as in synthetic materials.25 Here, we analyze theoretical and practical underpinnings of thisbehavior. We generalize the problem of mechanical work dissipationin polyproteins by considering the unfolding response of fingerprint(FP) domains  using receptor–ligand (RL) complexes as pullinganchors. Building on our previous Monte Carlo analysis,26 we confirm the FP biasing effect experimentallyand demonstrate how quantification of an experimentally observableparameter , representing the fraction of unbinding trajectoriesthat exhibit FP unfolding, can be used in a correction algorithm onbiased experimental data to recover the true unbiased energy landscapeparameters of FP domains. We apply this formalism to study the mechanicalproperties of native adhesive polyproteins, focusing on the FgB:SdrG-B1-B2system from S. epidermidis and theFIVAR-Dockerin:Cohesin system from Clostridium perfringens.Mechanicalforce can regulate protein structure and function indiverse ways. tension1.13−15 TWe first built artificialpolyprotein systems using the nanobody scaffold fused with FP domainsand validated our correction algorithm by comparison to unbiased FPunfolding data obtained with high-stability pulling handles. We thenapplied our correction algorithm to simulated data as well as experimentaldata from the SdrG:FgB system to correct the biased unfolding energylandscape parameters for the B2 domain. Finally, we considered theoptimal FP domain stability that maximizes mechanical work dissipationfor a given receptor and found a nonlinear behavior with a clear optimalvalue. This optimal FP stability represents a balance between strongFPs, which dissipate large amounts of work but frequently do not unfoldprior to RL breakage, and weak FPs that dissipate smaller amountsof work upon unfolding and stretching but do so more frequently priorto RL breakage.S. epidermidis and C. perfringens adhesins), the native FP domains exhibitstabilities at or nearthe optimal value for a specific range of loading rates. We arguethat by incorporating FPs with mechanical stability tuned slightlybelow their respective adjacent RL complexes, natural adhesins suchas the S. epidermidis SrdG-B1-B2 and C. perfringens FIVAR-Dockerin systems have evolvedoptimal sacrificial domains that can potentially serve as targetsin the development of antiadhesion therapies to combat infection.We show that for two pathogenic adhesive polyproteinsystems (Ḟ is the loading rate and k(F) isthe force-dependent off-rate. k(F) can take different functional forms, and most classically is givenby the Bell–Evans model29ko and Δx are the zero-force off-rate and position of the energybarrier, respectively; kB is the Boltzmannconstant; and T is the temperature. Assuming theBell–Evans29 expression for the force-dependentoff-rate (33 and we note that these expressions for k(F) are also compatible with the analysis algorithm presentedbelow.The process of FP domain unfoldingor RL complex rupture can be described as thermally driven escapeover an energy barrier accelerated under external force, with a probabilitydistribution of unfolding or rupture forces described by off-rate 2 and acp*FP(F) (p*FP(F) is therefore proportionalto the true FP unfolding force distribution pFP(F) multiplied by the cumulative probabilitythat the RL complex ruptures at higher forces than the FP unfoldingevent and divided by a renormalization constant eta, η  isderived, all nonstar quantities in the expression equations representthe true force distributions. That is to say, p*FP(F) refers to the biased distribution ofFP unfolding forces, pFP(F) refers to the unbiased distribution of FP unfolding forces, and pRL(F) refers to the unbiaseddistribution of RL rupture forces. We obtained the unbiased distributionof RL rupture forces by analyzing all RL rupture events from bothcurve classes shown  4, is a ct eta, η 5, to defes shown 2a.33 however, in many instances, a constant pullingspeed protocol is easier to implement experimentally. In the constant-speedscenario, the loading rate Ḟ is nonconstantbut rather a function of the force and contour length. As a result, pFP(F) and pRL(F), the value of η can be numerically computed fromthe integrals in Typically, theoretical treatment of dynamic force spectroscopyis performed under the assumption of a constant loading rate;Here, we show direct experimentalconfirmation of the FP biasing effect and validate our correctionalgorithm based on the minimization of residuals on η 2. By meaC. perfringens toxin complex.This domain has been used as a low-force FP domain in a previous SMFS-AFMstudy,34 where it showed a single-stepenergy barrier requiring ∼50 pN to unfold at 103–104 pN/s. As a second FP domain, we used the 4th F-actin cross-linker filamin domain from Dictyostelium discoideum (ddFLN4),35 containing a low-force intermediate state along its unfoldingpathway. For the high-strength RL complex, we used the SdrG:FgB interaction,and for the low-strength RL complex, we selected a single-domain camelidantibody  domain that forms a complex with thefluorescent protein mCherry. The VHH:mCherry low-strength RL complexruptures also at ∼60 pN at 103–104 pN/s34 and exhibits a rupture force distributionwith significant overlap with the FIVAR and ddFLN4 unfolding forcedistributions. We hypothesized that the weakness of the VHH:mCherryinteraction would lead to a strongly biased unfolding force distributionfor FIVAR and ddFLN4 and provide a good system on which to validateour correction algorithm.To build a test system, we designed artificial polyproteins containingRL complexes and FP domains with a significant degree of overlap intheir unfolding and rupture force probability distributions. As oneFP domain, we chose the FIVAR (found in various architectures) domainfrom a Escherichia coli. Full amino acidsequences of the proteins used in these studies are reported in the Supporting Information. The constructs were:(i) SdrG-ddFLN4-His-ybbR; (ii) VHH-ddFLN4-His-ybbR; (iii) FgB-FIVAR-His-ybbR;and (iv) mCherry-FIVAR-His-ybbR, where His indicates a poly(6x) histidinetag for affinity chromatography purification and ybbR indicates thegenetically encoded substrate for Sfp phosphopantetheinyl transferase36 for site-specific immobilization. Proteins werelinked to cantilever or coverglass surfaces through ybbR tags.39 Large datasets consisting of tens of thousands of single-moleculeAFM stretching and unfolding traces were acquired and screened forddFLN4/FIVAR unfolding. We measured FIVAR unfolding and the firstpeak of ddFLN4 unfolding events observed in bound complexes betweenconstructs (i:iii) and (ii:iv). These systems are identical in termsof the FPs but have different RL complexes used to apply tension acrossthe FPs. Both systems were well behaved in AFM-SMFS assays, generatinghundreds of usable SMFS traces exhibiting FP unfolding and RL ruptureevents, with contour length histograms that allowed domain assignment, generate a newclosed-form expression for the Bell–Evans probability distributionfunction of FIVAR unfolding forces, and newly predict the expectedη* values. Alternatively, the updated guesses could be passedinto a numerical Monte Carlo simulation on the order of 10,000–100,000force-extension curves to calculate the theoretical η*. Thisprocess was repeated until a close agreement between the theoreticallypredicted and experimentally observed η values was obtained.Depending on the force range and instrument sensitivity, the accuracyof this correcting strategy may be limited by experimental error,particularly for low-force systems (<50 pN). The correction approachwas validated on experimental datasets .The loading rate dependency of η for theVHH:mCherry (ii:iv) configuration was determined by the fraction offorce curves showing FIVAR unfolding across a range of pulling speedsfrom 400 to 3200 nm/s. Using the biased FIVAR dataset as input, weobtained initial guesses for the energy landscape parameters for theBell–Evans model with which we generated the closed-form Bell–Evansexpression for the probability distribution of FIVAR unfolding forces3. The prdatasets 3 and 4 w40 is not appropriate due to the lack of reversibilityand lack of regeneration of bonding that is required for the AFM setup.Nonspecifically adsorbed polyproteins will detach typically below1 nN. Therefore, for a subset of mechanostable FPs including B1 andB2, no direct unbiased measurement is possible. Here, we implementour correction algorithm on biased data from the B2 domain to obtaincorrected energy landscape parameters describing its mechanical stability.In the priorsection, we built an artificial system with designed overlaps in thedistributions of FP unfolding forces and RL complex rupture events.The high-force SdrG:FgB complex was sufficiently strong to unfoldboth FIVAR and ddFLN4 in all traces, so we could compare the resultsobtained with the correction algorithm to the true distribution. However,when measuring very mechanostable FP domains such as B1 and B2 fromSdrG adhesins, currently, no known molecular handle exists that issufficiently stable to provide an unbiased analysis. Covalent bonding,with a rupture force of 1–2 nN under AFM setup,E. coli: (v) FgB-Coh7-ddFLN4-ELP-His-ybbR; (vi): SdrG(N1-N2)-B2-ELP-His-ybbRand site-specifically linked them to a glass surface and cantileverthrough the terminal ybbR tags. We performed AFM-SMFS measurementsat pulling speeds of 100, 400, 1600, and 6400 nm/s and detected 813specific rupture events. To ensure specificity of the single-moleculetrajectories, two other FP domains (ddFLN4 and Coh7) were includedthat exhibit much lower unfolding forces  than the SdrG:FgB complex. While ddFLN4 and Coh7were unfolded in all of the obtained AFM traces . Using nonlinear least-squares fitting describedabove to minimize the residuals on η, we obtained correctedparameters of Δx = 0.076 ± 0.012 nm, ko = 5.1 × 10–14 ±6.3 × 10–14 s–1. As shownin We produced the following proteins using genetic engineering andrecombinant protein production in M traces 4a–c, the43 on two systems: (1) C. perfringens cohesin-dockerin RL complex  with its adjacentFIVAR domain 44  with its adjacent B2 domain  44 5a and (2–14 s–1) 5b.x parameter, which changed the most probable unfolding forceof the FP (Funf]) away from that of the WT system.We simulated the pulling experiments with and without the alteredFPs and calculated the work dissipation ratio while the FP stabilitywas scanned from low to high. This was done for 25 different Δx values for each FP/RL system under loading rate from 1to 1010 pN/s  produced stretching ensembles with workdissipation ratios very close to the theoretical maximum values onlywithin a given range of loading rates . This optimal value was achieved whenthe FP stability was situated slightly below the stability of theRL complex such that the ratio of most probable FP unfolding forceto most probable RL complex rupture force ([Funf]/[Frup]) was near 0.8, correspondingto η ∼ 0.95. With the inclusion of the optimized sacrificialdomain, the lifetime of the RL complexes can be enhanced under randomfluctuating mechanical loads from the ambient environment . We note thatat optimal values of η, the biasing effect is significant andthe energy dissipation ratio is highest. To investigate the influenceof linker length, we conducted numerical simulations also on systemswith mock sacrificial domains that have the same contour length butlacked a folded structure  . Priorwork has shown that the inclusion of compliant linkages can significantlyinfluence the dynamic strength of biomolecular interactions in a loading-rate-dependentmanner.46 The distribution of the simulated resultsis shown in Supporting Information Figures 3 and 4 for force ramp and constant pulling speed, respectively.We note that within a certain range of loading rates where the nativeFP shows the optimized energy dissipation, the inclusion of a stablemechanical fold could significantly improve the energy dissipationcompared to an unfolded linker sequence; however, unstructured linkersperformed as better dissipators than the folded dissipator withinthe regime where FP shows a low energy dissipation ratio .The Monte Carlo analysis 5 revealex and koff. This can be understood becausefor a fixed set of RL parameters, Δx of theFP influences the steepness of the loading rate dependency of FP unfolding,while the magnitude of the forces is dependent on both Δx and koff. Both parameterscan therefore influence the experimentally observed η values.Natural multidomain adhesive polyproteins must strike a balance thatmaximizes the average work dissipated by the given system to maintainadhesion. Our simulations also showed that high work dissipation forthe polyprotein system can extend the bond lifetime under conditionsof random velocity fluctuations and re-foldability of the FP. Thefact that natural adhesin systems from S. epidermidis and C. perfringens produce polyproteinscontaining FPs and RLs with matched parameters near the optimum withina specific range of loading rates suggests a mechanical selectionpressure could be at work in nature. In a similar way, other naturalsacrificial domains found in bone and muscle could be further investigatedunder different physiological loading schemes for potential enhancementof work dissipation in tissues or synthetic materials in the future.When proteins are mechanicallyunfolded with an RL interactionas an anchor point, the competition between unbinding and unfoldingpathways results in a biased distribution of unfolding forces forthe FP. By quantifying η in large SMFS datasets, we were ableto correct for this biasing effect and obtain corrected energy landscapeparameter estimations for unfolding of several domains of interest. We demonstrated the concept on synthetic dataas well as on an engineered system containing a VHH nanobody:mCherryinteraction, where both unbiased and biased distributions were experimentallyavailable. We then applied this algorithm to the FgB:SdrG-B2 systemfor which no sufficiently stable RL complex is available to obtainunbiased observations. Finally, we investigated the theoreticallyoptimal η value that achieves maximal dissipation of mechanicalwork on average for an ensemble of pulling trajectories. This optimalη reflects a balance between strong sacrificial domains thatdissipate large quantities of energy but do so infrequently, and weaksacrificial domains that dissipate small quantities of energy butdo so with every loading event. Correction of the biasing effect resultsin changes to parameter estimates for both ΔD. discoideum 4th filamin), FIVAR domain from C.perfringens, and Coh7 domain (seventh cohesin domain of CipA fromClostridium thermocellum) were inserted into a pET28a vector containingELP-HIS-ybbr using Gibson assembly, respectively. Construction of(v) and (vi) was introduced in a previous publication.34 Final open reading frames of all constructswere confirmed by Sanger sequencing (Microsynth AG). The Addgene informationof the plasmids (i to vi) and the complete sequences of all proteinconstructs used are listed in the Supporting Information.The constructs for AFM measurementswere (i) SdrG-ddFLN4-ELP-His-ybbR; (ii) Fgß-FIVAR-ELP-His-ybbR;(iii) SdrG-B2-ELP-His-ybbR; (iv) Fgß-Coh7-ddFLN4-ELP-His-ybbR;(v) VHH-ddFLN4-His-ybbR; and (vi) mCherry-FIVAR-His-ybbR. The plasmidpET28a_SdrG-B1-B2-HIS-HRV3C-ybbr and pET28a_ybbr-HIS-ddFLN4-8GS-FIVAR-Docwere kind gifts from Hermann Gaub’s lab at Ludwig-Maximilians-UniversitätMunich. The Staphylococcus epidermidis SdrG N2 and N3 domain genes,the Staphylococcus epidermidis SdrG B1 domain, ddFLN4 domain (E. coli BL21(DE3). Preculturesof 5 mL in LB medium containing 50 μg/mL Kanamycin, grown overnightat 37 °C, were inoculated in 200 mL of ZYM-5052 autoinductionmedia47 containing Kanamycin and grownfor 10 h at 37 °C. Bacteria were harvested by centrifugationat 4000g, and pellets were stored at −80 °Cuntil purification. The cell pellet was resuspended in Lysis Buffer TritonX-100,pH 8.0) including 100 μg/mL Lysozyme and lysed by sonication,followed by centrifugation at 16,000g for 30 minat 4 °C. The His6-tagged proteins were purified using a His-TrapFF column, followed by desalting using a His-Trap Desalting columnon AKTA Pure system followed by size exclusion. Protein concentrationswere determined by absorbance at 280 nm.All proteins wereexpressed in 48 In brief, Sulfo-SMCC was covalently bondedto the silanized surface of the AFM cantilever and the glass surfacefor constructs containing ELP included constructs, and a 5k Mal-PEG-NHSlinker was conjugated for non-ELP constructs, followed by conjugationof CoA on the surface. Then, the ybbR labeled fusion proteins wereconjugated to CoA using an SFP reaction. All measurements were conductedin TBS buffer  under a constant pullingspeed.Immobilizationof the fusion protein on the AFM cantilever as well as the glass surfacewas achieved as introduced in previous papers.X(t) was generated, by whichthe applied force F(t) could becalculated using a worm-like chain (WLC) model  model 7 with a H(t)  8 using aFti– Fti–1 = LR*(ti– ti–1), the timeseries could be generatedwith applied force loading rate LRFor a constant force loading rate mode (Force ramp) wherethe pullingforce is applied using a constant loading rate LR with respect totime following: k(F) was integrated overeach time interval k(F) can be drawn from β–1 = kBT. To test if thedissociation happens for the FP unfolding/RL complex rupture, thedissociation probability is compared to a random number between zeroand unity to test if the rupture or unfolding event occurs withineach time interval. When the FP domain unfolding event occurs, a releasedcontour length is added to the total molecular length while both forceand extension series are updated correspondingly. The extension ofthe released contour length after the unfolding events was simulatedfollowing Hooke’s law with a modulus at 90 pN/nm, which isthe stiffness of the AFM cantilever. For each system, 1000 curveswere generated. The aforementioned Monte Carlo simulations were performedusing Python, the code and corresponding instructions of which areavailable at https://github.com/Nash-Lab/Monte-Carlo-Methods.Then, the simulationof the dissociation process for FP unfoldingand RL rupture during the forced pull test was conducted within eachtime interval along the time axis until the RL complex ruptured. Toobtain the probabilities for the receptor–ligand dissociationand FP domain unfolding within each timestep, the force-dependentoff-rate To correct energy landscapeparameters by minimizing η residuals, a numerical calculationwas conducted to yield the rate-dependent η following