Sorghum bicolor (L.) Moench) and several other C4 grasses are associated with reduced lignin concentration, altered lignin composition and improved cell wall digestibility, which are desirable properties in biomass development for the emerging lignocellulosic biofuel industry. Studying bmr mutants has considerably expanded our understanding of the molecular basis underlying lignin biosynthesis and perturbation in grasses. In this study, we performed quantitative trait locus (QTL) analysis, identified and cloned a novel cinnamyl alcohol dehydrogenase allele (SbCAD2) that has an 8-bp deletion in its 5′-untranslated region (UTR), conferring the spontaneous brown midrib trait and lignin reduction in the sorghum germplasm line PI 595743. Complementation test and gene expression analysis revealed that this non-coding region alteration is associated with the significantly reduced expression of the SbCAD2 in PI 595743 throughout its growth stages. Moreover, a promoter-GUS fusion study with transgenic Arabidopsis thaliana plants found that SbCAD2 promoter is functionally conserved, driving a specific expression pattern in lignifying vascular tissues. Taken together, our results revealed the genetic basis of bmr occurrence in this spontaneous sorghum mutant and suggested the regulatory region of the SbCAD2 can be a target site for optimizing lignin modification in sorghum and other bioenergy crops.Brown midrib (bmr) mutants in sorghum ( In the renewable bioenergy industry, overcoming the intrinsic recalcitrance of biomass is critical for the development of lignocellulosic biofuel as a cost-effective alternative to fossil fuels2. Biomass recalcitrance is mainly due to the complex configuration of lignin polymer chains and the intertwined network of lignin and polysaccharides in plant cell walls3. In plants, the highly interwoven cell wall matrix rigidified by lignin is crucial for their structural integrity, water conduction and pathogen resistance5. Hence, as a major impediment to plant biomass utilization and an essential component of the secondary cell wall, lignin has become a main research object in plant biology and its biosynthetic pathway has been extensively studied in the past several decades. In general, cell wall lignin is oxidatively polymerized primarily from three types of alcohols (monolignols), which are synthesized in cytosol from phenylalanine through successive deamination, reduction, hydroxylation and methylation steps5. Knowledge from the well-delineated monolignol biosynthetic pathway has led to the successful genetic manipulation of lignin content and composition in bioenergy grasses7. Recently, in order to minimize developmental defects in lignin-modified plants, lignin modification strategy has evolved from simple perturbations of the general monolignol biosynthetic pathways to coordinated orchestrations of the lignin synthesis, deposition and integration into the cell wall network8. Therefore, a profound knowledge and advanced understanding of the underlying regulatory mechanisms of lignin production would benefit the long-term goal of manipulating cell wall structure in biomass feedstocks based on our needs.Sorghum is one of the premier biomass feedstocks for biofuel production because of its high biomass yield, outstanding drought tolerance and efficient nutrient usage11. In grasses, this trait is characterized by the reddish-brown pigment accumulated in leaf midribs and stems during the vegetative stage. In earlier years, this distinct pigmentation was found to be associated with higher ruminant digestion rate and thus became a desired feature in livestock forage development13. Later, the property of reduced lignin content in bmr mutants was appreciated by plant geneticists and utilized for identifying candidate genes for manipulating the lignin production in grasses14. A number of mutagenized bmr mutants of sorghum have been characterized and the corresponding genes involved in specific enzymatic steps of monolignol biosynthetic pathway have been identified in recent years18. For instance, bmr6 mutant, originally generated from a diethyl sulfate mutagenesis sorghum population, was found to be associated with reduced cinnamyl alcohol dehydrogenase (CAD) activity19. CAD is a specialized enzyme of the alcohol dehydrogenase family involved in the conversion of the cinnamaldehydes into alcohols, the monomeric precursors of lignin. Downregulation of CAD genes generates atypical lignin polymers with the incorporation of phenolic aldehydes and becomes a promising strategy to improve cell wall digestibility22. Later on, a nonsense mutation in a sorghum CAD gene (SbCAD2) was identified to be responsible for the bmr6 phenotype. Specifically, the nonsense mutation truncates the coding region of SbCAD2 prior to the conserved NADPH-binding and C-terminal domains and consequently, abolishes the function of the encoded protein17.Brown midrib (bmr) is a visual trait first documented in maize over eighty years ago and later mutagenesis-induced in sorghum and pearl millet23. Stacking different bmr mutations in sorghum has an additive effect on lignin content and cellulose-to-ethanol conversion24. Therefore, there are some recent efforts focusing on characterization of novel bmr sorghum lines derived from EMS (ethyl methanesulfonate)-mutagenized populations with the aim to incorporate new sources into the forage and biomass feedstock improvement26. In summary, most sorghum bmr mutants studied so far are from mutagen-induced populations, and no spontaneous bmr phenotypes in sorghum have been characterized in detail at the molecular level.Fiber digestion tests and field evaluation performed on sorghum varieties carrying the mutagenized bmr mutations found that they generally show higher digestibility and inferior agronomic performance relative to their wild-type counterparts, even though the effects of mutations are not uniformly expressed across different genetic backgrounds and are influenced by environmental conditionsSbCAD2 is responsible for this novel spontaneous bmr phenotype. This deletion results in the down-regulation of SbCAD2 expression in PI 595743 in a mechanism that is different from that underlying the reduced expression of SbCAD2 in the bmr6 lines. Furthermore, we found that the function of SbCAD2 promoter is conserved in both sorghum and Arabidopsis and this deletion region is implicated in the transcriptional regulation of SbCAD2 expression in lignifying tissue. We expect that this alternative allele of SbCAD2 gene will expand the repertoire of genetic resources for biomass improvement in sorghum, and more importantly, provide new insights into the complex underlying regulatory mechanism of the lignin biosynthetic pathway in grasses.In this study, we focused on PI 595743, a sorghum germplasm line showing a distinct bmr trait without any observable growth and developmental defects. Phenotypic evaluation confirmed the lignin deficiency in its brown vascular tissues. We next used QTL mapping, DNA sequencing and complementation test to identify that an 8-bp deletion in the 5′ UTR of Compared to the non-mutant sorghum plants with pale green midrib, PI 595743 first exhibits the characteristic reddish-brown color in the midrib at the 4, 5-leaf stage. The brown coloration accumulates with the expansion of the leaf blade and gradually fades as plants mature. The base of leaf on the abaxial side has the highest intensity of bmr color. Strong brown pigmentation was also observed throughout the stem of PI 595743 Fig. .Figure 1CAD-deficient mutants in Arabidopsis27. Moreover, when subjected to Maule staining, the pink-red coloration prominently presented in the BTx623 sclerenchyma cells surrounding vascular bundles was missed in the mutant samples  protein that catalyzes the last step of monolignol biosynthetic pathway, was present in this region. In addition, Sobic.004g071000 (SbCAD2) had been previously identified as the gene underlying the mutagenized bmr6 phenotype in sorghum. Thus, we selected this gene as a promising candidate for further study. Moreover, this selection was supported by the result of our previous phloroglucinol staining which indicates more aldehyde groups in PI 595743 tissues.Combining the mapping information with sorghum genome sequence database, forty-eight genes have been localized in the region defined by markers SASb4546 and SASb4581. These genes, together with their locations, lengths and functional annotations, are given in Table 1 progeny plants showed the characteristic brown color in their midribs, suggesting these two mutated phenotypes cannot be complemented to each other and they could be either the same mutant alleles, or different mutant alleles of the same gene.A complementation test was performed by crossing PI 595743 with the bmr6 mutant line to determine whether these two mutants are caused by the same gene or two different genes. All twenty-five FSbCAD2. However, an 8-bp nucleotide deletion (CCTCTCGG) was found within its 5′-untranslated region located 93 bp upstream of the start codon  was performed to investigate the SbCAD2 promoter of non-bmr line BTx623 is active in Arabidopsis and its expression pattern is conserved in the lignifying vascular tissues, transgenic Arabidopsis plants containing a pSbCAD2::GUS construct were developed , the second enzyme in the monolignol pathway, exhibit severe dwarfism and sterility31. Similar deleterious defects were also observed in the diethyl sulfate (DES)-induced bmr lines of sorghum, precluding the subsequent genetic study on those mutants9.Developing brown midrib mutant lines and identifying the genetic basis of lignin deficiency in these mutants are of increased interest due to their potential to reduce biomass recalcitrance. There are more than ten enzymatic steps involved in the monolignol biosynthetic pathway, leading to the synthesis of monolignol precursors for lignin polymerization33 and transgenic lines with down-regulated CAD activity35 were generally associated with reduced lignin content and/or altered lignin composition change, even though there were some reported inconsistencies partly due to functional redundancy of CAD paralogs or incomplete disruption of CAD expression. In sorghum, the CAD-deficient bmr6 mutant showed reductions in lignin content, altered lignin composition and an improved cell wall digestibility24. Despite the substantial impact on lignin biosynthesis, agronomic evaluation found that the bmr6 mutant was not associated with significant negative impacts on plant fitness in comparison with its near-isogenic counterpart25. In the current work, a spontaneous sorghum bmr mutant, PI 595743, showed a modest decrease in lignin content and dramatic change of lignin composition in certain lignified cell types, in agreement with the aforementioned fact that monolignol biosynthesis is highly plastic as to allow CAD-deficient plants to form lignin polymers directly from cinnamyl aldehydes. The accumulation of aldehydes and reduction of the S lignin subunit in PI 595743 were revealed by phloroglucinol staining and the Maule staining, respectively. These histochemical results provide the first clue that the CAD enzymatic activity is likely affected in PI 595743. Gene expression assay further confirmed the down-regulation of SbCAD2 gene during the development of PI 595743 plants. The significant reduction of CAD activity due to a nonsense mutation was reported in bmr617. Based on the allelic variation, it may prove of interest to examine to what extent the CAD activity is impaired in PI 595743. Furthermore, comparative evaluation of different CAD mutants under the same genetic background, for example, within the near-isogenic lines would be a good starting point to study whether genetic variants in the SbCAD2 gene have different effects on lignin composition, biomass digestibility and the overall agronomic performance.Due to the importance and plasticity of the last step of monolignol pathway, the impacts of CAD disruption on cell wall properties have been intensively studied in several plant species. CAD-deficient mutantsSbCAD2 in its vascular tissues17. In the present work, based on collective evidences from histochemical analysis, QTL mapping, association study and complementation test, an 8-bp deletion in the 5′ UTR of SbCAD2 was linked to the dark-brown pigmentation and the significant reduction of SbCAD2 expression in the spontaneous mutant PI 595743. Thus, an obvious question from these results is: how does this deletion in an untranslated region affect the expression of SbCAD2 and lead to a mutated phenotype? As a fundamental structural and regulatory region of eukaryotic genes, 5′ UTR mainly plays a role in the regulation of mRNA translation, providing a novel layer of coordinated control of gene expression37. Parts of the 5′ UTR may also contain regulatory elements and may be part of the promoter. 5′ UTR-mediated regulation of transcript abundance and translational efficiency has been reported in plant development and stress responses40. In the case of PI 595743, the 8-bp deletion within the 5′ UTR could affect its qualitative features, such as length, GC content and potential for secondary structure formation, associated with the translational regulation. There is also a possibility that this deletion is involved in the transcriptional regulation of SbCAD2 by interfering with potential binding sites, an interaction mechanism totally different from the mRNA decay mechanism underlying the reduced expression of SbCAD2 in the bmr6 mutant. Further studies on heterologous expression of a reporter gene fused with this mutated 5′ UTR or promoter deletion analysis are needed to dissect the association between this specific deletion and lignin pathway perturbation.Previous research on the bmr6 mutant revealed that a nonsense mutation-mediated mRNA decay mechanism was very likely involved in the downregulation of CAD2 gene reflects the conservation of mechanism that underlies the transcriptional regulation of monolignol biosynthetic pathway in higher plants. The conservative property of lignin biosynthesis in plants has been investigated and discussed previously from different perspectives43. Evolutionarily speaking, the signals controlling vascular expression of lignin biosynthetic genes are more likely to be highly conserved in higher plants since lignin biosynthesis is an early adaptation feature for vascular plants to survive in the terrestrial environment44. In addition, the maintenance of conserved motifs in many lignin biosynthetic genes suggested a common catalytic mechanism might be shared during the process of lignification in plants45.The active expression of GUS gene in the lignifying tissue of Arabidopsis plants driven by the promoter of the sorghum 46. Knowledge gained from this study could open an avenue for us to decipher the regulatory aspects of the SbCAD2 gene and reveal the occurrence of bmr phenotype and lignin production in grasses at the transcription and post-transcription level.Lignin biosynthesis is a highly coordinated process that involves the expression of multiple monolignol genes and the coordinated regulation of transcription factors6 recombinant inbred line (RIL) population was developed by crossing BTx623 and PI 595743. Specifically, PI 595743 (pollen donor) was crossed with BTx623  to obtain heterozygous F1 seeds, and the F1 plants were self-pollinated to produce the F2 segregating population. A set of 188 F6 RILs were obtained from the F2 family by the single-seed descent method.The plant materials used in this study included the spontaneous sorghum bmr mutant (PI 595743), the elite inbred line (BTx623) and the bmr6 mutant. PI 595743 is a photoperiod insensitive conversion of SC 1201 selected from the World Sorghum Collection. It was developed in Texas, United States and used as a breeding material because of its early maturing, enhanced height and forage potential. In our study, an F47. Briefly, sections were stained with phloroglucinol-HCl solution consisting of 1.0% (w/v) phloroglucinol, 3.7% (w/v) HCl, and 10% (v/v) ethanol for 1 min and mounted onto microscope slides for observation. Maule reagent was used to examine the sinapyl alcohol monomers (S lignin) content and localization in vascular tissues as described previously48. Sections were prefixed in 4% glutaraldehyde for 1 h and rinsed with sterile water. After that, sections were immersed in 1% (w/v) potassium permanganate solution for 5 min followed by a water rinse. They were then treated with 10% HCl (w/v) for 5 min, rinsed with water, and mounted on microscope slides in concentrated NH4OH. Stained sections were immediately observed under bright-field lighting on a Nikon 80i microscope and photographed.Stem internodes collected from two developmentally-equivalent parental lines were hand-sectioned to a thickness of 200 μm using double-edge razor blades. Phloroglucinol stains the coniferylaldehyde end-groups present in lignin, forming a red-pink color in acidic conditions50. Briefly, triplicate samples of 10 mg powder from stem and midrib tissues were sequentially washed with 500 μL of water, ethanol, chloroform and acetone for 30 min, respectively. Washed samples were placed in glass 20 mL scintillation vials and heated overnight at 70 °C. Two and a half microliters of 25% AcBr solution was added to each vial and incubated at 50 °C for 2 h with occasional swirling. After cooling to room temperature, each sample was transferred into a 50 mL volumetric flask holding 10 mL of 2 N sodium hydroxide, and 12 mL of acetic acid. More acetic acid was used to bring the solution to the fixed volume. Samples were settled at room temperature overnight and the absorbance of the resultant solution at 280 nm was determined using a spectrophotometer. The lignin percentage of the dry sample was calculated from the regression equation of lignin content in herbaceous samples51.For total lignin quantification, stem and midrib materials collected from PI 595743 and BTx623 plants at the end of vegetative stages were dried and pulverized into powder with metal beads in a vibratory solid sample homogenizer. Acetyl bromide (AcBr)-soluble lignin was quantified using the reported procedurePhenotyping was conducted around the time when the brown pigmentation in midrib reaches its maximum intensity, approximately 6 weeks after the planting. The leaf midrib phenotype of each RIL was visually scored and confirmed by the data from three replicates.6 RIL using a modified CTAB protocol52. Initially, 1019 simple sequence repeat (SSR) markers in sorghum were used to survey their polymorphisms between BTx623 and PI 595743. Among them, 121 were identified as polymorphic and used for genotyping the entire population. PCR products were analyzed by ABI 3730xl DNA Analyzer (Applied Biosystems) and scored using GeneMarker version 4.0 (Soft Genetics LLC).For genotyping, genomic DNA was extracted from seedlings of two parental lines and each F53 with a logarithm of odds score (LOD) of 3.0 and maximum linkage threshold of 40 cM. The recombination frequency between linked loci was transformed into genetic distance  using the Kosambi’s function. The output files were imported into QTL Cartographer version 2.553 for QTL analysis. Single Marker Analysis, Composite Interval Mapping (CIM) and Multiple Interval Mapping (MIM) analyses were performed by following the lab procedure52.A linkage map was constructed by MAPMAKER/Exp 3.0www.phytozome.net/sorghum) to define the start and end position of the physical interval. All genes within this interval were subject to functional annotation and protein homology detection. A gene was identified as a real candidate only if there was experimental evidence that it is involved with brown pigmentation in vascular tissue, lignin biosynthesis or secondary cell wall formation.After the major QTL was localized, the nucleotide sequences of two markers flanking this region were used in BLAST searches against sorghum genome database version 3.1.1  in PI 595743 were sequenced as overlapping fragments generated by high-fidelity PCR amplification. Primer information is given in Table Approximately 2 kb of upstream sequence immediately before the coding start codon and the 5.7 kb genomic sequence of SbCAD2 featured in the spontaneous bmr mutant PI 595743, non-bmr BTx623 and bmr6, samples were prepared from each line at the 3,4-leaf stage, the 6, 7-leaf stage and near the end of vegetative stage (emergence of the flag leaf). Fresh leaf tissues from the same location in each plant were harvested, and immediately ground in liquid nitrogen. Total RNA was isolated using TRIzol reagent (Invitrogen) following the manufacturer’s instructions, and 1 μg aliquots were treated with DNase and then reverse transcribed. The transcriptional profile was analyzed by qRT-PCR using the SYBR Green PCR Master Mix (Applied Biosystems) with the Biorad Real-Time PCR System. Primer specificity was verified by cloning and sequencing PCR products obtained from BTx623 cDNA. The melting curve analysis and the evaluation of primer amplification efficiency were performed before running the cDNA samples. Relative expression levels were calculated from the cycle threshold using 2−ΔΔCt method54. A sorghum β-tubulin gene (Sobic.002g350400) was used as the internal control. The data were the average of three biological replicates. Primers used for qRT-PCR are listed in Table To analyze the expression pattern of SbCAD2 promoter in lignifying tissue and establish a platform for studying the regulatory mechanism underlying SbCAD2 expression, a construct of the full length SbCAD2 promoter (pSbCAD2) fused to the β-glucuronidase (GUS) reporter gene (uidA) was generated. Specifically, the full length promoter (1976 bp of upstream sequence before the ATG) was PCR amplified from BTx623 genomic DNA by using region-specific primers and the high-fidelity polymerase mix. The PCR product was purified and cloned into the promoterless GUS vector pBI101, producing a fusion construct by following the manual instructions of the In-Fusion HD Cloning Kits . The insertion was PCR amplified and confirmed by sequencing before transformation.In order to explore the function of Agrobacterium tumefaciens strain LBA4404 using the freezing/heat shock method. Transgenic Arabidopsis plants carrying the pSbCAD2::GUS expression cassette were generated by Agrobacterium-mediated transformation using the floral dip method56. In order to confirm the specific expression conferred by the SbCAD2 promoter, a transformation using a CaMV 35 S::GUS construct (pBI 121) was performed in parallel.The full-length promoter-GUS fusion construct was introduced into 1 and T2 plants from different lines was investigated as described in the protocol57. Briefly, the basal region of the floral stems from each equivalently developed plants were collected and incubated for 12–24 h at 37 °C in GUS staining solution: 100 mM sodium phosphate (pH 7), 5 mM EDTA (pH 8), 0.5 mM ferrocyanide, 0.5 mM ferricyanide, 0.5 mg/mL X-Gluc (5-bromo-4-chloro-3-indolyl-β-d-glucuronide). A series of ethanol with different concentration  were used to replace the staining solution and remove chloroplast pigments. Crossed sections (80–150 μm) were observed for blue pigment deposition with a Nikon 80i microscope and photographed with an affiliated CCD camera.Histochemical location of GUS activities in transgenic TSupplementary Information


Cell populations display heterogeneous and dynamic phenotypic states at multiple scales. Similar to molecular features commonly used to explore cell heterogeneity, cell behavior is a rich phenotypic space that may allow for identification of relevant cell states. Inference of cell state from cell behavior across a time course may enable the investigation of dynamics of transitions between heterogeneous cell states, a task difficult to perform with destructive molecular observations. Cell motility is one such easily observed cell behavior with known biomedical relevance. To investigate heterogenous cell states and their dynamics through the lens of cell behavior, we developed Heteromotility, a software tool to extract quantitative motility features from timelapse cell images. In mouse embryonic fibroblasts (MEFs), myoblasts, and muscle stem cells (MuSCs), Heteromotility analysis identifies multiple motility phenotypes within the population. In all three systems, the motility state identity of individual cells is dynamic. Quantification of state transitions reveals that MuSCs undergoing activation transition through progressive motility states toward the myoblast phenotype. Transition rates during MuSC activation suggest non-linear kinetics. By probability flux analysis, we find that this MuSC motility state system breaks detailed balance, while the MEF and myoblast systems do not. Balanced behavior state transitions can be captured by equilibrium formalisms, while unbalanced switching between states violates equilibrium conditions and would require an external driving force. Our data indicate that the system regulating cell behavior can be decomposed into a set of attractor states which depend on the identity of the cell, together with a set of transitions between states. These results support a conceptual view of cell populations as dynamical systems, responding to inputs from signaling pathways and generating outputs in the form of state transitions and observable motile behaviors. Cells in a population are not all alike. The differences between cells impact how each cell responds to stimuli, with implications for development and disease. How do cells change between these functionally important states over time? This question is difficult to answer using molecular biology, because these methods destroy cells in order to observe them, preventing us from observing the same cell more than once. Cells in culture display a diverse set of motility behaviors that can be observed non-destructively over time. We have developed software to quantify these behaviors, and used this tool to identify cell motility states and quantify the changes in cell motility states over time. Using this approach, we identify that cancerous fibroblasts behave similarly to normal fibroblasts, but prefer some behaviors to others. This suggests cancerous transformation may lead to changes between states, rather than just creating new ones. Applying this analysis to muscle stem cells, we measure the rate of change from the stem cell to progenitor state for the first time. We are also able to determine if changes in behavior state are externally driven or random, demonstrating the utility of observing cell behaviors to study changes in cells over time. Within any group of cells, each individual cell is not necessarily like its neighbors. These differences often have functional significance, with cells at different points along the phenotypic spectrum exhibiting distinct behavior . This haRecent advances in single cell assays have allowed for detailed, quantitative descriptions of individual cells at the molecular level. Single cell sequencing technologies in particular have uncovered heterogeneity at both the transcriptional and epigenetic level , 9. In mIn addition to defining cell states to account for population heterogeneity, we also seek to understand the transitions between states, because those transitions reveal the logic of the cellular control system. In seminal work, Waddington introduced the conceptual model of an ‘epigenetic landscape’ governing cell phenotype decisions, akin to a potential energy landscape in a physical system , 16. In While existing molecular assays such as single-cell RNA-sequencing can provide detailed information about a cell population’s heterogeneity, these assays are generally destructive and restricted to a single time point for analysis. Methods have been developed to infer cell state lineages from observations at a single time point , 19, butCells in culture have a diverse behavioral repertoire. Each cell may exhibit motion, dynamic morphology changes , 20, andRecent work from several groups has elucidated the regulatory priciples governing cell shape definition , 25 and Cell motility behaviors are inherently related to the morphological state of a cell –35. DiffCell motility is a particularly dramatic cell behavior, but it is difficult to examine quantitatively. Traditional cell motility assays rely on a binary filtration of cells based on a functional test, such as crossing a membrane barrier. Timelapse microscopy has also been appreciated for decades as a means of tracking and quantifying cell motility at the single cell level –40. ThesHere, we present Heteromotility, a software tool for quantitative analysis of cell motility in timelapse images with a diverse feature set. In addition to commonly calculated features such as distance traveled, turning, and speed metrics, Heteromotility provides features that allow for comparisons to models of complex motion, such as Levy flights and fractal Brownian motion, and estimate long-term dependence within a cell’s displacement distribution. This feature set creates a high-dimensional space representing the possible phenotypes of cell motility. These features may be useful for multiple downstream applications, including supervised classification of different motility phenotypes, and unsupervised definition of different motility behaviors, both of which we demonstrate here. Our tool is modular, and we also provide tools to map the high-dimensional motility feature space into a low dimensional state space, tools to quantify changes in cell motility phenotypes over time as transitions in state space, and tools to consider the stochastic or directed nature of these transitions. These tools allow the dynamics of cell behavior states to be elucidated, in addition to simply identifying heterogenous phenotypes.We demonstrate that Heteromotility analysis is sufficient to discriminate between simulations of several models of motion. Applied to wild-type and transformed mouse embryonic fibroblasts (MEFs), Heteromotility analysis reveals a shared set of motility states between the two systems, in which transformed cells preferentially occupy a more motile state. In mouse myoblasts and MuSCs, phenotypically distinguished motility states are revealed. MuSCs display a series of progressively more motile states, suggesting states of activation. Quantifying transition dynamics within this state system over time reveals that MuSCs transition through state space toward a progressively more activated, myoblast-like motility phenotype. Viewed through the lens of myogenic activation, we are able to follow the activation dynamics of individual MuSCs for the first time. Applying probability flux analysis, we find that the MuSC motility state system breaks detailed balance, quantitatively confirming that these state transitions occur in an ordered and predictable sequence, as in a computing device.r2 as a metric of fit. Monotonicity is also considered for the distribution of points, using Spearman’s ρ2. In some instances, cells have been proposed to have a directional bias when making turns  with successive displacements that are not necessarily independent. The Hurst parameter H describes the self-similarity of a fBm process, with the interval 0 < H < 0.5 describing a process with negatively correlated successive displacements , H = 0.5 describing non-correlated, independent successive displacements (Brownian motion), and 0.5 < H < 1 describing positively correlated successive displacements (large displacements are more likely to follow large displacements). The Heteromotility software estimates the Hurst parameter as a metric of long range memory using Mandelbrot’s rescaled range method (see Supp. Methods) . As. Asτ as H = 0.9) were generated with a range of track lengths. Samples with a range of sizes (members per class) were redrawn from these large populations three times per sample size/track length parameterization. We then analyzed the simulated data to determine if the feature set is sufficient to place each model in a distinct region of a joint feature space.In principle one could devise an infinite number of motion descriptors. How can we determine whether a given set of motion features is sufficient to capture meaningful aspects of motion? To test whether the feature set outlined above is sufficient to distinguish biologically relevant models of motion, we simulated and analyzed cell paths generated by four distinct motion models: unbiased random walks, biased random walks, Levy flights, and fractal Brownian motion with long range memory (t-Stochastic Neighbor Embedding (t-SNE), a visualization method that embeds high-dimensional data into a low-dimensional map, to generate 2D projections of our high dimensional feature space  FGF2, and the remaining 10 were imaged in growth media with [0 ng/mL] FGF2. Additional details are available in the Supplemental Methods.All images were performed in a temperature and CO2 controlled unit at 37°C and 5% COhttps://github.com/cellgeometry/heteromotility) and in the Python Package Index (PyPI). Detailed descriptions of the algorithms are provided in the Supplemental Methods.DIC images were segmented using custom segmentation algorithms, optimized for each of the systems we investigated. Tracking was performed with a modified version of uTrack . Code isS1 Text(PDF)Click here for additional data file.S1 Fig(A) Heteromotility workflow diagram and (B) a table of the complete feature set.(TIF)Click here for additional data file.S2 Fig(A) Simulated models of motion are segregated by unsupervised heirarchical clustering, as displayed in representative a heatmap of hierarchically clustered (Ward’s linkage) simulated motion paths  based on Heteromotility features. Color labels on the left mark a sample’s True Class. Effective separation of the True Classes indicates effective detection of different phenotypes by unsupervised clustering. Two-dimensional (B) PCA and (C) ICA visualization of the simulated motion paths to provide an intuition for the linearity of motility state space and performance of traditional linear dimensionality reduction techniques. Only high (30) dimensional PCA spaces are used for analysis. ICA is not used for any downstream analysis. (D) Representative t-SNE visualizations of simulated motion models with different sample sizes and track lengths, labeled with ground truth classes. Models occupy distinct regions of state space under all sample size and track length variations. (E) Representative t-SNE visualizations of simulated motion model groups with the underlying parameters for each motion model varied. Parameters for each condition shown are displayed above the t-SNE map. (F) Unsupervised clustering accuracy (Ward’s linkage) as a function of parameter variations to the underlying simulations. Performance decreases as expected when parameters are set in a manner that decreases the distinctness of the models. For example, performance is lower when the bias parameter for biased random walks is set to a low value, close to an unbiased random walk, or when the fractal Brownian motion index is set to the same index displayed by a random walker (H = 0.5). Performance is high across other conditions tested.(TIF)Click here for additional data file.S3 Figr2 values for linear regression models fit between the Local Cell Density Index and each feature pairwise. No features in any system display a relationship with a meaningful effect size (max r2 ≈ 0.03).(A) Cumulative variance explained for each dimensionality of principal component space across MuSC, MEF, and Myoblast systems. (B) Strength of relationships between our Local Cell Density Index and each of the Heteromotility features, displayed as overlapping histograms of Pearson’s (TIF)Click here for additional data file.S4 Fig(A) Representative t-SNE visualizations, MycRas and wild-type cluster distrobutions, and selected cluster feature values for three “splits” from a Round Robin analysis. In the Round Robin analysis, analyses were performed on 4 experiments  leaving 2 experiments out in an iterative fashion for each possible combination of experiments. MEF cluster distributions and properties are reproducible across all combinations. (B) Aggregate confusion matrix for SVM classifiers trained in a Round Robin fashion, such that 4 experiments were used for training and 2 for evaluation for all combinations of 4 experiments. SVMs classify MycRas and wild-type cells with 70% accuracy and do not demonstrate a prediction bias for one class over the other. (C) Distribution of Round Robin Classification Accuracies for SVMs trained on each Round Robin split. (D) Top 10 most important features for Round Robin Classification Accuracy using SVM classifiers. Features importance is determined as the decrease in classification accuracy when an SVM is retrained without a given feature as input. The Top 10 features were selected based on the mean decrease in Round Robin Classification Accuracy across Round Robin splits. (E) t-SNE visualization of all MEF cells analyzed, labeled with their experimental origin.(TIF)Click here for additional data file.S5 FigC. Five bias parameter values were tested in a linear distribution in the range  around the bias parameter C ≈ 0.5 we found for the optimal SVM by Grid Search. Reduced feature sets were selected using only the top N% of features based on ANOVA F-scores. (B) Cluster distributions and cluster feature values for clustering of MEFs with reduced feature sets. Feature sets were reduced to the top N% based on ANOVA F-scores. Behavioral clusters are still identifiable and MycRas/wild-type dependent state distribution is preserved with a single feature.(A) Round Robin classification accuracy is significantly, positively correlated to the proportion of features utilized. Points represent mean Round Robin Classification Accuracy for a given parameter set of N% of features and a value for the SVM bias parameter (TIF)Click here for additional data file.S6 FigClustergrams of myoblast feature space using several hierarchical clustering linkages. The assigned cluster label for each linkage map is displayed in a color coded column on the left hand side of each heatmap. Ward’s linkage was used for downstream analysis.(TIF)Click here for additional data file.S7 FigFGF2 does not influence MuSC motility phenotypes, and MuSC motility states reflect progressive states of activation. (A) t-SNE visualization of MuSC motility space with FGF2 treated and untreated color labels. (B) Occupancy of MuSC motility states in FGF2 treated and untreated conditions. (C) Pseudotime analysis displaying a reduced dimensional representation of MuSC and myoblast motility space (DDRT) with a minimum spanning tree plotted to mark the pseudotime axis. Pseudotime analysis attempts to find a temporal axis through an ergodic process observed at a single time point by fitting a minimum spanning tree (MST) to a reduced dimensional representation of multidimensional data. The longest axis of the MST is assumed to represent the temporal axis of the ergodic process. MuSC states are clearly ordered in a progressive sequence, moving toward the myoblast phenotype over pseudotime. (D) Scatterplot of MuSC/Myoblast transition vectors, demonstrating that transition vectors are primarily along the first principal component and slightly skewed in the positive direction.(TIF)Click here for additional data file.S8 Figtau = 20 and 15 course-grained bins. Course-grained probability flux analysis (cgPFA) of (B) myoblast (FGF2-), and (C) MuSC (FGF2+) motility states with subpaths of length τ = 20 time points (130 minutes) and 15 course-grained bins per dimension. Each unique combination of bins between PC1 and PC2 is considered as a unique state. Arrows represent transition rate vectors, calculated for each state bin as the vector mean of transitions into the neighboring states in the von Neumann neighborhood. Arrow direction represents the direction of these transition rate vectors, and arrow length represents transition rate vector magnitude. Underlying colors represent the vector divergence from that state as a metric of state stability. Positive divergence indicates cells are more likely to leave a state, while negative divergence indicates cells are more likely to enter a state. (D-I) State occupancy visualizations of the same course-grained PCA presented for cgPFA analysis. The number of cells that occupy a given state for at least one time unit is represented in the third dimension of the landscape and by the heatmap colors.(A) Three-dimensional representation of the MycRas MEF state divergence surface as measured by cgPFA using (TIF)Click here for additional data file.S9 Figtau ∈ {20, 25, 30} and binning resolution k ∈ {5, 10, 15, 20, 30} across all cellular systems. Representative visualizations across these parameter ranges are presented. Both (A) MycRas and (B) wild-type MEFs retain the qualitative metastable ‘basin’ appearance across time scales. As binning resolution decreases below k = 10, the structure of the state space is obscured. At higher resolutions of k, more bins little net divergence are present. (C) Myoblast cgPFA state spaces likewise retain a metastable ‘basin’ appearance across time scales. (D) MuSC state spaces retain a metastable ‘valley’ surrounded by unstable ridges across time scales. At higher binning resolutions of k, an unstable ridge within the metastable valley becomes more apparent.Course-grained PFA analysis as demonstrated in (TIF)Click here for additional data file.S10 FigMuSC motility state dwell time analysis reveals rapid transitions, longer dwell times in higher occupancy states, and roughly exponentially distributed dwell times. Dwell times vs. total number of observed cells for each occupied state in course-grained PCA space for  FGF2- MuSCs,  FGF2+ MuSCs in two-dimensional PCA space, and  FGF2- MuSCs and  FGF2+ MuSCs in PCA spaces where detailed balance is broken. Dwell time distributions relative to the binned samples from a fitted exponential distribution for (C) FGF2- MuSCs and (F) FGF2+ MuSCs in two-dimensional PCA space, and (I) FGF2- MuSCs and (L) FGF2+ MuSCs in PCA space where detailed balance is broken.(TIF)Click here for additional data file.S11 Figτ ∈ {20, 25, 30}. (A) The results of detailed balance breaking are robust across settings of this time scale parameter. At each time scale, the MuSC system breaks detailed balance, while the MEF and myoblast systems do not. Heatmaps display the five most unbalanced transitions for each defined cgPFA space. tau, course-grained bin, and stride parameters are listed above each heat map. (B) To demonstrate that detailed balance is present in the MuSC system on short time scales, we performed ND-cgPFA using the same number of temporal windows size tau = 20, but overlapped them with a single unit stride of s = 1. In this scheme, each window is only 1 time unit different than it’s neighbor, such that only 2 time units of difference are present between the initial and final time window. On this short time scale, MuSC systems do not break detailed balance.ND-cgPFA as presented in (TIF)Click here for additional data file.S12 FigHierarchical clustering based probability flux analysis of (A) a Levy flight simulation transitioning to a random walk, (B) an invariant random walk simulation, (C) myoblasts (FGF2+), (D) myoblasts (FGF2-), (E) MycRas MEFs, (F) WT MEFS, (G) MuSCs (FGF2+), and (H) MuSCs (FGF2-). The matrix displays transitions in state space as values in a matrix. Rows of the matrix correspond to an initial cell state (t0 state) and columns correspond to a destination state (t1 state). The value of each bin represents the number of times a state transition was observed. Symmetrical bins about the diagonal represent reciprocal pairwise transitions, with one ‘forward’ transition and one ‘reverse’ in each pair. The identity line represents “self” or non-transitions. MuSCs show a less balanced distribution than either MEFs or myoblasts by the binomial test for pairwise transition balance. Pairwise transitions breaking detailed balance are outlined in red.(TIF)Click here for additional data file.S13 Fig(A) Representative random samples of 80% of MuSCs with a 3 cluster partition (Ward’s linkage) applied. Note cluster separation along a common axis, robust to resampling. (B) Representative random samples of 80% of MuSCs with a 4 cluster partition (Ward’s linkage) applied. Note separation of clusters along multiple axes in some samples, and a single axis in others. The 4 cluster partition is not robust to resampling.(TIF)Click here for additional data file.S1 VideoNumeric labels indicate the motility state of each cell. Color coded circles indicate the positions visited by each cell over time.(AVI)Click here for additional data file.S2 VideoNumeric labels indicate the motility state of each cell. Color coded circles indicate the positions visited by each cell over time.(AVI)Click here for additional data file.S3 VideoNumeric labels indicate the motility state of each cell. Color coded circles indicate the positions visited by each cell over time.(AVI)Click here for additional data file.S4 VideoNumeric labels indicate the motility state of each cell. Color coded circles indicate the positions visited by each cell over time.(AVI)Click here for additional data file.S5 VideoNumeric labels indicate the motility state of each cell. Color coded circles indicate the positions visited by each cell over time.(AVI)Click here for additional data file.S6 VideoNumeric labels indicate the motility state of each cell. Color coded circles indicate the positions visited by each cell over time.(AVI)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.


Previously, research groups statistically modelled the effect of 10 individual nutrition-specific interventions targeting the critical first 1000 days of life from conception, on lives saved and costs incurred in countries with the highest burden of stunted children. However, primary research on the combined effects of these interventions is limited. Our study directly addresses this gap by examining the effect of combinations of 5 This community-based cluster randomised trial (c-RCT) compares 4 intervention combinations against one comparison arm. Intervention combinations are: 1) Behaviour change communication (BCC) on maternal nutrition during pregnancy, exclusive breastfeeding, and complementary feeding, along with prenatal nutritional supplement (PNS) and complementary food supplement (CFS); 2) BCC with PNS; 3) BCC with CFS; and 4) BCC alone. The comparison arm receives only routine health and nutrition services. From a rural district, 125 clusters were selected and randomly assigned to any one of the five study arms by block randomisation. A bespoke automated tab-based system was developed linking data collection, intervention delivery and project supervision. Total sample size is 1500 pregnant women, with minimum 1050 resultant children expected to be retained, powered to detect a difference of at least 0.4 in the mean LAZ score of children at 24 months, the main outcome variable, between the comparison arm and each intervention arm. Length and other anthropometric measurements, nutritional intake and other relevant data on mother and children are being collected during enrolment, twice during pregnancy, postpartum monthly till 6 months, and every third month thereafter till 24 months.preventive nutrition intervention approaches addressing the critical window of opportunity to mitigate childhood stunting. The results will provide robust evidence as to which bundle(s) can have significant effect on linear growth of children. Our study also will have policy-level implications for prioritising intervention(s) tackling stunting.This c-RCT explores the effectiveness of bundles of NCT02768181).The study was retrospectively registered on May 2, 2016 and is available online at ClinicalTrials.gov (ID: The online version of this article (doi:10.1186/s12889-017-4281-0) contains supplementary material, which is available to authorized users. Sylhet division, the north-eastern region [Globally in 2013, 161 million children under the age of five years U-5 children) had a height-for-age Z score more than 2 standard deviations (SD) below the median of WHO Multicentre Growth Reference Study (MGRS) Child Growth Standard (termed ‘stunting’), and half of these children resided in Asia , short s childrenn region .Although unaddressed by the Millennium Development Goals, reduction of stunting prevalence became the focus of several high-profile nutrition initiatives such as Scaling Up Nutrition  , World HChildhood stunting is considered to have in utero origins . The firIn the Lancet Maternal and Child Nutrition Series 2013, Bhutta et al. (2013) statistically modelled the effect of 10 nutrition-specific interventions on lives saved and economic costs in 34 countries containing the majority of the children with stunted growth . They supreventive interventions to create our own interventions bundles, based on Bhutta et al.’s list considering feasibility of scale-up in low resource settings and targeting the first 1000 days of life (from conception to two years of age). Our interventions include, a) Behaviour change communication (BCC) on nutrition and health-related practices during pregnancy; b) BCC on exclusive breastfeeding (EBF) for postnatal first 6 months; c) BCC on age-specific complementary feeding (CF) with continued breastfeeding thereafter till 23 completed months; d) Nutritional supplementation during pregnancy (PNS) with preventive doses of micronutrients, and partial provision of protein and lipids; e) Nutritional supplementation for children (CFS) during 6 to 23 completed months of age, with preventive doses of micronutrients, and partial provision of protein and lipids. In essence, this randomized controlled trial provides a crucible to see how different nutritional interventions interact when delivered in bundled packages in community settings to affect linear growth of the child from conception to two years of age compared to the comparison arm where routines practices will run unhindered.We have adapted five This study aims to test the effectiveness of the intervention bundle(s) on improving length-for-age Z score (LAZ) of children at two years of age. We hypothesised that our intervention bundle(s) would cause a change of at least 0.4 in mean LAZ of children, translating to at least 30% reduction in stunting in that arm(s), compared to that in the comparison arm.). The cohort of the mother-child dyads will be followed-up over the intervention period of ~36 months starting from recruitment to 24 months of child’s age.This cRCT evaluates the effectiveness of 4 different combinations of the selected pre- and post-natal nutrition-specific interventions for improving children’s linear growth, compared to the comparison arm with usual practices. The three types of BCC are combined into one ‘BCC’ intervention and delivered universally in all four intervention arms. Profile of the four intervention arms are – intervention arm 1: BCC with PNS and CFS; intervention arm 2: BCC with PNS; intervention arm 3: BCC with CFS; intervention arm 4: BCC alone.  of Habiganj district. These two sub-districts have a total of 20 unions (lowest administrative unit). We excluded 8 unions, 3 being in hard-to-reach areas  and 5 having intensive nutrition intervention projects implemented by other non-government organisations (NGOs). The remaining 12 unions had enough population to cover the desired sample size. Each union was then divided into clusters, each cluster comprising of ~450 households or ~2000 population (average 2–3 villages). We selected five clusters or multiples of 5 clusters from each union, 125 clusters in total following the cluster exclusion criteria detailed in Table We purposively selected two adjacent sub-districts (Each study cluster comprised of an average population of 2000 and necessary adjustments were considered for cluster randomization. Crude birth rate (CBR) in rural Bangladesh in 2011 was 23 live births per 1000 population . TherefoSylhet division [Several assumptions were considered for the sample size calculation . The firdivision . Second,division , 15% losWe enrolled 10 pregnant women in each intervention cluster and 20 in each comparison cluster, following the inclusion and exclusion criteria for participant eligibility  developed by Nutriset™, packed in ~20 g sachets, is provided to pregnant women. The formulation contains vegetable fat (soy), skimmed milk powder, peanuts, vitamin and mineral complex, sugar, stabilizer: fully hydrogenated vegetable fat, and antioxidant: tocopherols. An additional file details the components  visits and caregivers of children under two years of age receives IYCF counselling during postnatal care visits within 42 days and sick child management visits at health facilities and by NGO workers (if available) . HoweverCounselling and supplement sachets are delivered through our specially trained Community Health Workers (CHWs). Their tasks are supervised and monitored by two layers of field supervisors – a team of Field Supervisors (FSs), and a Field Research Assistant (FRA). Minimum educational qualification of the CHWs is Higher Secondary School Certificate (HSC) completed, while the FSs and the FRA have completed their Bachelor’s degree. The intervention team was given intense counselling training in three phases, and monthly meetings are held for field-related troubleshooting and as refresher courses. Supervisors provide daily feedback to associated CHWs during on-site counselling supervision.At least 4 antenatal counselling sessions are delivered during pregnancy. Following live birth notification, 8 counselling sessions are delivered within 48 h and 7–14 days of birth, and at completion of every month till 6 months. Thereafter, counselling is delivered every third month till postnatal 23 completed months .The primary outcome measure will be the LAZ of children at 24 months of age based on WHO MGRS 2006 child growth reference. This will be calculated from the child’s age in months and length on associated ages. Length is measured at age 7–10 days, then monthly from 1 to 6 months, and at 9Body weight of mothers is measured during enrolment and on the 6th and 9th month of gestation. Gain in weight will be compared among homogenous gestational ages and initial nutritional status of mothers. Weight is measured with a Tanita™ weighing scale (precision 100 g).Body weight of children is measured at birth, on 7–10 days, then monthly from 1 to 6 months, and every third month thereafter till 24 month, using Salter scales (precision 10 g).Detailed ingredients of the pregnant mothers’ dietary intake on the previous 24-h are collected, through an interviewer-administered open 24-h dietary recall form adapted from the FAO dietary diversity guidelines , during Data on IYCF practices (breastfeeding and complementary feeding) are collected through a structured IYCF questionnaire, employing 24-h  and 7 daWHO-recommended complementary feeding practices include introduction of solid, semi-solid or soft foods; minimum dietary diversity, meal frequency and acceptable diet; and consumption of iron-rich or iron-fortified foods from postnatal 6 completed months . This inBackground characteristics of study participants: Information on demographic and socio-economic status (SES), family members, reproductive and morbidity history of pregnant women were collected using a structured questionnaire . HousehoWater sanitation and hygiene (WASH) and Knowledge attitude and practice (KAP): A questionnaire on the core indicators on water, sanitation and hygiene (WASH) was developed based on a standard manual for WASH . Woman’sChildhood morbidity: Morbidity, especially diarrhoea, directly impedes growth, while better hygiene practices lower infectious disease burden . TherefoAdditional anthropometric measurements: Mother’s height is measured during recruitment for body mass index (BMI) calculation during early pregnancy. Mother’s mid-upper arm circumference (MUAC) (precision 1 mm), infant’s head circumference (during 1–6 moths age) and infant’s MUAC (during 7–24 months) are collected during follow-up visits, for associated z-score calculations.All questionnaire-based data and anthropometric measurements are collected by trained data collectors. Anthropometric measurements are taken following measurement-specific standard operating procedure . MeasuriA bespoke automated Project Management Information System (MIS) has been developed linking data collection and intervention delivery through android-based tablet (handheld)-PC with a central database where progress can be monitored by the field supervisors and central staff. On pregnancy enrolment through the tab, an android platform-based application automatically generates subsequent prenatal visit plans and tools at pre-specified schedules and tasks of CHWs and data collectors (intervention modules for CHWs and questionnaire for data collectors). Similarly, birth is registered in the tab immediately upon notification. To ensure post-partum data collection within 24 h of delivery, a mobile phone-based birth-notification system has been established. Enrolled pregnant women and their family members are continuously encouraged to notify birth by text message or voice calls as early as possible, preferably within six hours of birth. Registration of live births then generates appropriate plans and tools for postpartum visits by CHWs and data collectors. The web-linked desktop dashboard system is used to monitor activities/performance of CHWs and data collectors in real time by field supervisors and the central team.Empty supplement sachets are collected and supplement tracking is carried out in each visit by the CHWs. Besides, we are assessing supplement compliance using a structured questionnaire with some open questions with queries on respondents’ attitude and practice towards the antenatal and complementary food supplements provided to them. We would collect similar data for checking compliance of complementary supplements to children aged 6 months to 24 months (in associated arms).The BCC modules set in the tablets are customised for each CHW. Date and time of each visit is automatically recorded as the CHW proceeds with the module. The module for each visit has several sub-topics linked to associated details, and timing of these sub-topics is also automatically recorded. These measures ensure an automated machine-based monitoring system from which BCC delivery coverage can easily be tracked and calculated.Data analysis to detect change of the primary outcome (mean LAZ) will be conducted with length measured at 1, 3, 6, 9, 12, 15, 18, 21 and 24 months of age using t-tests assuming LAZ will satisfy the normality assumption. Longitudinal assessment of significance using lag time of stunting (mean length > −2SD below median of WHO reference population) will be done by the log rank test, followed by fitting a Cox proportional hazards model for each intervention arm to determine the change in risk of stunting compared to the comparison arm. Multiple linear regression will be employed to quantify the effect of intervention in each intervention arm compared to the comparison arm in terms of mean LAZ change and some secondary continuous outcome measures including changes in mother’s weight, birth weight, diarrhoea morbidity. Logistic regression will be used on binary outcome variables which comprise most of our secondary outcomes measures (e.g. – EBF and breastfeeding initiation within 1 h of birth). All these models will be controlled for possible confounders  if randomisation of the clusters does not control for differences in these factors at baseline. For regression models, we shall consider random effects of clustering. All analysis will be intention-to-treat. Quantitative data analysis will be done using Stata SE 14.2 .preventive interventions, adapted from the Lancet’s modelled intervention list , delivered in different bundles to improve the LAZ score from conception to two years of age in a food-insecure area of rural Bangladesh.Our primary study aims to investigate the effects of 5 nutrition-specific One of the major strength of this study is its depth (multiple community-friendly evidence-based intervention packages) and breadth (first 1000 days with interventions directed at both mother and child). The results will attempt to clarify the effects of counselling combined with prenatal nutritional and/or complementary food supplementation on linear growth of the child. In addition, our study will also explore the interventions impact on nutritional intake during pregnancy, gestational weight gain, birth weight and IYCF practices. The cluster RCT design in a community setting will offer robust evidence on the effectiveness of the bundles compared to the comparison arm where routine practices will run unabated. The relatively homogenous study population in a food-insecure area would further strengthen our inferences, as we would expect minimal inter-cluster differences that would otherwise potentially confound associations.We are also one of the few studies in Bangladesh using a bespoke digital platform for intervention delivery and monitoring of coverage. Android-based handheld devices are being used by CHW to automate planning of visit schedules as well as aid counselling sessions by providing the appropriate BCC content based on the gestational age and subsequently, age of the child. Visual aids and video demonstrations of good practices included in the electronic counselling modules are expected to result in improved interaction and retention of key messages by the participants. Field level android-based devices are web-linked to a central server to leverage the opportunity for real time monitoring of community health workers performance and coverage of intervention delivery. Thus, this study will contribute to the growing body of implementation research on benefits and challenges of integrating electronic platforms in delivering counselling and supplemental interventions in a community setting.Recently, the government of Bangladesh undertook significant efforts to digitize service delivery in all spheres of health systems including frontline and community level health care providers who are responsible for delivering nutrition interventions . This trA limitation of our study includes not being able collect biological samples from study participants due to funding constraints; this would have allowed us to investigate potential biological mediators of the effect of nutrients as well as exploring inherited differences in metabolism predisposing to the risk of stunting. Our study also does not look at knock-on effects beyond 2 years of age.We anticipate that the results from this cRCT will have policy-level implications in prioritizing a set of interventions when addressing stunting - whether it is behaviour change communication only or combined with prenatal and/or post-natal nutritional supplementation.Recruitment has been completed. Intervention and data collection is ongoing.Additional file 1:Composition of LNS for pregnant women. (DOCX 16 kb)Additional file 2:Composition of LNS for children. (DOCX 17 kb)


In vitro studies demonstrated that CSL362 potently induced antibody-dependent cell cytotoxicity (ADCC) of AML blasts including CD34+CD38−CD123+ LSCs by natural killer cells (NKs). Importantly, compared with healthy donor (HD) NKs, NKs drawn from AML patients in remission had a comparable ADCC activity against leukemic cells; of note, during remission, immature NKs were five times higher in AML patients than that in HDs. Significantly, we report a case where leukemic cells were resistant to autologous ADCC; however, the blasts were effectively lysed by CSL362 together with donor-derived NKs after allogeneic hematopoietic stem cell transplantation. These studies highlight CSL362 as a promising therapeutic option following chemotherapy and transplant so as to improve the outcome of AML patients.Despite the heterogeneity of acute myeloid leukemia (AML), overexpression of the interleukin-3 receptor-α (CD123) on both the more differentiated leukemic blast and leukemic stem cells (LSCs) provides a therapeutic target for antibody treatment. Here we present data on the potential clinical activity of the monoclonal antibody CSL362, which binds to CD123 with high affinity. We first validated the expression of CD123 by 100% (52/52) of patient samples and the correlation of NPM1 and FLT3-ITD mutations with the high frequency of CD123 in AML.  Allogeneic hematopoietic stem cell transplantation  is considered definitive consolidation therapy in first or later CR, albeit at the expense of high morbidity and mortality due to infections and graft versus host disease;4 the predominant benefit of allo-HSCT is considered to be the effect of the immune-mediated graft versus leukemia that occurs post transplant. Novel therapies with increased efficacy as compared with chemotherapy alone and decreased toxicity associated with allo-HSCT are clearly needed for the treatment of AML.In the past 40 years, the standard treatment of acute myeloid leukemia (AML) has relied on cytotoxic chemotherapy combinations; despite changes in the drugs being used, there has been little improvement in outcomes. With current induction chemotherapy regimens complete remission (CR) occurs in up to 80% of patients;5 Among the various potential antigen targets for antibody-based AML therapy, CD123  has attracted much attention because of its high expression in AML and in particular on leukemic stem cell (LSCs).8 In general, LSCs have an inherent resistance to traditional chemotherapeutics associated with their stem cell nature; their persistence following chemotherapy is responsible for disease relapse.12 A number of different approaches for targeting CD123 are being investigated, either using its toxin-modified natural ligand, small molecules to inhibit receptor signaling or specific monoclonal antibody.15 It has previously been reported that antibodies against CD123 can mediate cytolysis of AML cells and in particular of LSCs.17 Although active, these antibodies were of murine origin and lacked the ability to efficiently recruit highly active human effector cells. More recently, a second-generation anti-CD123 antibody (CSL362) has been developed. CSL362 was engineered towards human IgG (humanized) and to have increased affinity to the Fc receptor CD16 on natural killer (NK) cells. This antibody has been shown to effectively induce antibody-dependent cell-mediated cytotoxicity (ADCC) of AML blasts in vitro and in AML xenograft models.18 Of interest was our observation that autologous NK cells from a patient with chronic myeloid leukemia blast crisis-induced CSL362-mediated cytotoxicity to the same extent as allogeneic healthy donor (HD) NK cells.19In the last 15 years, an increasing body of evidence has shown that engineered antibodies can improve the outcome of patients with cancer, including AML.21 Of note, it has been found that NK cells developing post chemotherapy and post transplant can have an immature phenotype; it has been suggested that these immature post-transplant NK cells have a reduced ability to kill recipient blast cells.24 In the present study we found that post chemotherapy autologous NK cells and NK cells from HDs produced comparable lysis of AML blast cells treated with CSL362. The results strongly encourage the clinical development of CSL362 as a novel therapeutic antibody for AML patients.NK cells provide a natural immunity against cancer. In AML, a role for NK cells in controlling disease is supported by the association of improved outcome of patients who have high levels of NK cells following allogeneic stem cell transplant.2 for 3 days and cytarabine 100 mg/m2 (age ⩾60 years) or 200 mg/m2 (age <60 years) by continuous infusion daily for 7 days. CR was defined as the presence of normal erythropoiesis, granulopoiesis and megakaryopoiesis, and <5% leukemic blasts in the bone marrow, and PB absolute neutrophil count ⩾1 × 109/l and platelet count ⩾100 × 109/l. PB samples from remission patients were collected at varying time points after being in the first CR for at least 1 month  samples of all AML patients and HDs were obtained following informed consent as approved by the research ethics board of the University Health Network. PB mononuclear cells (PBMCs) were separated by Ficoll  density gradient centrifugation. Fifty-two patients  with newly diagnosed AML treated by the Division of Medical Oncology and Hematology, Princess Margaret Cancer Center between April 2007 and January 2013 were enrolled in the study for assessing CD123 expression. The diagnosis of AML was made by expert clinical hematopathologists according to the morphological and immunological criteria of the National Cancer Institute expert panel and World Health Organization guidelines. Twenty patients in the first CR were enroled in ADCC-mediated blast depletion assays. The characteristics of these patients are shown in onth see .5), CD34-APC (581), CD33-v450 (WM53) and CD38-PE-Cy7 (HB7) were co-stained with CD123-PE. All antibodies were purchased from BD Biosciences. A CD45dim/SSClow gate was used to limit the analysis of AML bulk cells.25 Geometric mean fluorescence intensity (MFI) values of CD123 measured using FlowJo  were normalized to the MFI of the residual normal lymphocytes within each sample, which were negative for CD123. Total 52 samples’ MFI ratios (MFI blast/MFI lymphocyte) were subsequently analysed for CD123 expression intensity. Samples with CD123MFI ratio ⩾2.0 were regarded as positive.The expression of CD123 was analyzed by flow cytometry (BD FACSCanto II) using PE-conjugated anti-CD123 antibody . To determine CD123 expression on leukemic bulk and subsets of blast, CD45-FITC . The enriched NK cells were resuspended in RPMI medium containing 10% fetal bovine serum for immediate use in ADCC assay. Before the use for ADCC, an aliquot of these enriched NK cells (CD3−/CD56+) were further characterized for purity and the proportion of mature NK cells (CD56low) and immature NK cells (CD56high) by flow cytometry.PBMCs were stained with monoclonal antibody combinations of CD3-PE-cy7, CD56-FITC and CD16-PE  to characterize the NK cell phenotype and CD1626CSL362 and the corresponding IgG1 isotype control antibody BM4 were produced by CSL Limited, Parkville, Australia. CSL362 was developed from the murine anti-CD123 monoclonal antibody 7G3 in a stepwise process of humanization, affinity maturation and Fc-engineering. Two amino acid mutations (S239D and I332E) were introduced into the Fc region to enhance NK-mediated cytotoxicity of the antibody. The characterization of CSL362 activity has been reported in previous studies.− population. For such samples, we used a combination of markers such as CD33, CD34 and CD38 to help clearly identify the leukemic blast cells. Apart from control cultures incubated with no antibody, pretreating the blast with BM4 was the nonspecific antibody control. The specific lysis mediated by CSL362 was calculated by the formula: remaining cells (%) of BM4−remaining cells (%) of CSL362)/remaining cells (%) of BM4.In this study we refer to the cell-mediated blast depletion assay with CSL362 as ‘ADCC’, which was tested as follows: AML samples obtained at diagnosis were pretreated with CSL362 at 10 μg/ml (30 min) and incubated with enriched NK cells at an effector to target cell ratio (E:T) of 10:1 for 24 h in RPMI/10% fetal calf serum at 37 °C; residual AML cells were analyzed by flow cytometry. The CD45dim/SSClow population was used as the standard gate for AML blast cells. In some cases it was difficult to analyze the blasts, as the blast population was very close to the CD45highCD123t-test. Differences between three or more groups were compared using a one-way analysis of variance. For all analyses, mean±s.e.m. values are given, and *P<0.05 and **P<0.01, unless otherwise stated.Graphpad Prism 6.0  was used for statistical analyses and graphs. Differences between two groups were compared using an unpaired + blast cells were observed in 69.23% (36/52) of AML samples and all expressed CD123. A CD34+CD38−/low blast subset typically containing LSCs27 was observed in 17.31% (9/52) of the tested AML samples and all expressed CD123. No statistical difference was observed between the subsets in either expression frequency or expression intensity of CD123 in all AML samples   . These f+ and CD45 dim/CD123+, respectively. The utility of this approach to identify consistent depletion of CSL362-treated leukemic blasts is shown for Pt.130429  and 56.56% . Focusing on the CD34+ subset, the net effect of treatment with CSL362 was a specific lysis of the CD34+ cells by 46.48% (autologous) and 59.91%  relative to the control BM4 antibody. Furthermore, there was a significant killing of cells in the LSC population defined by CD34+CD38−/low CD123+. Of note, there was equivalent killing of the CD34+CD38−/low and the CD34+CD38+ population of blast cells.As there was variable killing of AML cells by the combination of autologous NK cells and CSL362, we were interested in determining whether this was due to a defect in the patients’ own NK cells or an intrinsic resistance of the leukemic blast cells. NK cells were isolated from HDs and tested for their ability to kill leukemic blast cells in the presence or absence of CSL362 as described above. Although in most cases we observed roughly the same degree of killing by autologous and allogeneic NK  cells, there were significant exceptions. First, although autologous killing tended to be high across samples, there was one case (Pt 130363) in which no killing was observed when autologous NK cells were used. However, the same AML blasts were specifically killed by allo-NK cells see . Second,The above variability in the lysis of target cells is highlighted by one case in which we had the opportunity to study NK cells from the patient pre and post allogeneic stem cell transplant. The leukemic blast cells (130363) were resistant to killing by autologous NK cells collected pretransplant. However, donor-derived NK cells obtained from the patient post-transplant were highly efficient in killing the leukemic cells. Similarly, NK cells from a HD also killed 130363 blast cells .29 A desired agent should effectively and specifically target both bulk AML cells and in particular the residual LSCs that are thought to be responsible for relapse and poor disease outcome.31Treatment options after induction of remission for AML generally consist of intensive consolidation chemotherapy followed by a watch and wait period or allo-HSCT. Although transplant reduces the occurrence of relapse, patients may die due to complications or have a reduced quality of life due to the effects of graft versus host disease. Unfortunately, a large proportion of patients who do not undergo a transplant due to lack of a suitable donor, comorbidities or age not compatible with transplant, or patient choice continue to have a high rate of relapse. Hence, there remains a need for safe, tolerable and effective therapy to maintain/consolidate AML remission, especially for patients at high risk of relapse.16 Indeed, our present results are in line with those data regarding the high expression of CD123 on bulk AML cells and the CD34+CD38− fraction, which typically contains LSCs. As one of the aims of this study was to determine the degree of CSL362-enhanced NK cell killing of AML cells as it relates to the cell surface expression of CD123, we focused on the mean expression value/intensity as well as the proportion of cells above a certain threshold. In keeping with other studies,28 and in contrast to a report by Jordan et al.,32 we did not observe that CD123 expression was higher on the LSC containing CD34+CD38− blasts than bulk leukemia cells. The variable findings between groups might be explained by different type of samples tested (bone marrow or PB), different methods of expression investigation (flow cytometry or immunohistochemistry), different equipment, different gating strategies, different reagents and different size of cohorts evaluated in the studies. Regardless, all studies are in agreement that CD123 is expressed on cells within the stem cell compartment of the leukemic population and hence is a desirable therapeutic target. We further correlated CD123 expression with four disease characteristics. In accordance with a previous report,6 we observed that CD123 is overexpressed by most AML cells irrespective of subtypes investigated in the study, suggesting that targeting this molecule could be of wide benefit. Our data also confirmed a recent study showing no correlation between CD123 expression and risk groups.28 Likewise, that same study reported the correlation of higher levels of CD123 expression with NPM1 and FLT3-ITD mutations, which is consistent with our findings and other studies34 Consequently, any study targeting CD123 should be sure to ensure inclusion of such patients and be powered to assess this group separately.In recent years, numerous reports have documented the presence of high interleukin-3 receptor-α (CD123) expression on the surface of AML blasts and the AML-LSC fraction, but not on normal HSCs. This identifies CD123 as an attractive target for antibody-based immunotherapy.37 Following on the demonstrated importance of NK cytotoxicity, CSL362 was developed as a second-generation anti-CD123 antibody, which has over 100-fold increased affinity for CD16 on NK cells through its modified Fc domain. Indeed, our previous evaluation of neutrophils, monocytes, macrophages and NK cells in ADCC assays revealed that NK’s are the major effector cell responsible for CSL362-mediated cytotoxicity.17 Moreover, binding of CSL362 to NK cells leads to evidence of NK cell activation as shown by the upregulation of the degranulation marker CD107a, a prerequisite for NK cytolysis.17 In the current study, CSL362 or BM4 was added to the bulk blast cell population, without the addition of excess NK cells. Although there was blast depletion with CSL362, no killing was observed with the control BM4 antibody. This indicates that CSL362 can mediate its function through autologous NK cells in the presentation sample (data not shown). In AML, the functional NK cell compartment is decreased at initial presentation;39 however, in remission numerous reports have documented that by four weeks post treatment NK cells show significant recovery, being among the earliest lymphocytes to come back.41 In keeping with this, we observed that NK cells isolated from PB drawn 1 month or more after achieving the first CR had recovered to normal proportions. Combined, these findings help to dispel the concern that too few NK cells may be present in remission patients for CSL362 to be effective. Meanwhile, our studies indicate that the recovered NK cell population post chemotherapy contains a higher proportion of immature NK cells. This has been observed previously,22 where it was suggested that these cells might be deficient in cytolytic activity since immature NK cells are reported to be capable of cytokine and chemokine production but low killing ability; this is in contrast to mature NK cells that are considered to have robust cytotoxicity.42 However, the studies presented here indicate that NK cells developing post chemotherapy in AML patients are equal to HDs’ NKs in terms of cytolytic activity via CSL362-meidated ADCC despite the high frequency of CD56brightCD16−low immature NKs. Given the heterogeneity of AML, we believed it to be essential to test CSL362 against more than a few primary AML samples. Here we tested a collection of 20 samples that included six common subtypes of AML. Our data demonstrate that PB NK cells of AML patients post chemotherapy are capable of killing autologous blast cells in the presence of CSL362 across a range of AML subtypes.Previous studies have demonstrated that NK cells are an important mediator of AML cell killing, particularly in the post stem cell transplant setting.in vivo when there is a low level of residual disease during the remission state. We are further encouraged by our finding that CSL362-mediated specific lysis of the CD34+CD38−CD123+ subset of AML blasts, which in general, more precisely, defines the CD34+ cellular component that contains LSCs.43 This is of importance, as these LSCs are believed to be responsible for disease relapse44 and therefore elimination of these cells is crucial for reducing the chance of disease recurrence. As the residual LSCs have proven themselves to be resistant to standard chemotherapy, probably due to their reduced cycling and residence within the protective bone marrow niche, an alternative form of cell killing is required in order that they be eliminated; killing by CSL362 in conjunction with NK cells provides such an opportunity.The observation that NK cells could kill autologous AML blasts treated with CSL362 in the presence of a large number of blast provides encouragement that NK cells will be able to eliminate CSL362 binding AML cells 46 Our studies suggest that the inclusion of the lineage-specific antibody CSL362 could further enhance the effectiveness of this approach for all patients. In addition to the use of CSL362 for the above adoptive immune-therapy, our finding that blasts of Pt.130363 were resistant to killing by autologous NK cells, but were sensitive to donor NK cells derived from the patient post allo-HSCT suggests that CSL362 could be used in the post-transplant setting to potentially enhance the therapeutic benefit of the transplant, particularly in settings where the post transplant relapse rate is high. The addition of CSL362 post allogeneic transplant may also allow for different anti-GvHD approaches allowing for reduced morbidity of this complication. These and other results provide the rationale for testing the tolerability and potential clinical efficacy of CSL362 in AML. It is currently being tested in a Phase I study of CSL326 in patients with CD123+ AML in remission .Our results are particularly striking when one compares ADCC mediated by CSL362, and autologous and allo-NK cells. The finding that for 18/20 samples autologous NKs obtained during remission induced ADCC that was comparable to HD allogeneic ADCC suggests that most AML patients may gain clinical benefit from the administration of CSL362 during remission by prolonging the time to relapse or even preventing relapse. For those patients whose autologous NK cells did not kill CSL362-treated blasts, allogeneic cells were effective. Already, haploidentical NK cells are being used in clinical trials to reduce relapse of AML.


There is a need for the development of synthetic biology methods and tools to facilitate rapid and efficient engineering of yeast that accommodates the needs of specific biotechnology projects. In particular, the manipulation of the mitochondrial proteome has interesting potential applications due to its compartmentalized nature. One of these advantages resides in the fact that metalation occurs after protein import into mitochondria, which contains pools of iron, zinc, copper and manganese ions that can be utilized in recombinant metalloprotein metalation reactions. Another advantage is that mitochondria are suitable organelles to host oxygen sensitive proteins as a low oxygen environment is created within the matrix during cellular respiration.. We have also generated a toolkit comprising various promoters, terminators and selection markers that facilitate the generation of multigenic constructs and allow the reconstruction of biosynthetic pathways within Saccharomyces cerevisiae. To facilitate the specific expression of recombinant proteins within the mitochondrial matrix, we have also included in the toolkit an array of mitochondrial targeting signals and tested their efficiency at different growth conditions. As a proof of concept, we show here the integration and expression of 14 bacterial nitrogen fixation (nif) genes, some of which are known to require specific metallocluster cofactors that contribute to their stability yet make these proteins highly sensitive to oxygen. For one of these genes, nifU, we show that optimal production of this protein is achieved through the use of the Su9 mitochondrial targeting pre-sequence and glycerol as a carbon source to sustain aerobic respiration.Here we describe the adaptation of a modular cloning system, GoldenBraid2.0, for the integration of assembled transcriptional units into two different sites of the yeast genome, yielding a high expression levelWe present here an adapted GoldenBraid2.0 system for modular cloning, genome integration and expression of recombinant proteins in yeast. We have produced a toolkit that includes inducible and constitutive promoters, mitochondrial targeting signals, terminators and selection markers to guarantee versatility in the design of recombinant transcriptional units. By testing the efficiency of the system with nitrogenase Nif proteins and different mitochondrial targeting pre-sequences and growth conditions, we have paved the way for future studies addressing the expression of heterologous proteins in yeast mitochondria.The online version of this article (10.1186/s12896-017-0393-y) contains supplementary material, which is available to authorized users. Saccharomyces cerevisiae is a single celled yeast commonly used for biotechnological and synthetic biology applications that has the ability to either ferment or respire to grow depending on the available carbon source(s). Using yeast as a chassis for biotechnology is impactful as it serves as a starting point for more complicated engineering projects in higher eukaryotes that share many of its metabolic and cellular characteristics. Several modular cloning methods exist for engineering yeast, such as MoClo-YTK  cluster biosynthetic protein NifU, which is fundamental to the synthesis of metallocluster cofactors of nitrogenase enzymes. We demonstrate consistent expression of GAL1 promoter or constitutive expression using eight promoters that span a high dynamic range. A subset of these constitutive promoters showed different expression profiles during fermentative versus respiration growth. The promoters TPI1p, PYK1p, PGI1p, TDH2p and HXT7p resulted in higher expression in cultures with glycerol provided as the carbon source, facilitating respiration . Functionally, both of these GoldenBraid standards are fully compatible, with GB3.0 introducing a few new structural elements. GB3.0 includes a new set of destination vectors with increased in planta transformation efficiency and a CamR domestication vector, all of which work seamlessly with GB2.0 and our toolkit. In contrast to other cloning methods such as Gibson assembly, GoldenBraid requires the removal of specific Type IIS restriction sites from the parts in order for the GB reaction to proceed (termed “domestication”). Thus, the creation of a library of interchangeable and shareable parts is a key component of GB assembly, in contrast to Gibson assembly. Our toolkit has similar advantages to other modular assembly cloning toolkits used for yeast, such as MoClo-YTK and yGG [URA3 locus [URA3, LEU2, TRP1, and/or HIS3 loci [We developed our yeast adapted GoldenBraid toolkit based on the GB2.0 standard. The current GoldenBraid standard is GB3.0 and incorporates new bioinformatics tools through the GoldenBraid website  List of primers and templates used for the domestication of parts. (DOCX 17 kb)Additional file 2: Table S2.(.doc) Sequences of primers used (DOCX 15 kb)Additional file 3: Figure S1.(.doc) Sequences of parts used for transcriptional unit assembly. (DOCX 25 kb)Additional file 4: Figure S2.yeastgenome.org/blast-sgd; matrix BLOSUM62) of the AOH sequences cloned in the adapted vectors and yeast strain W303 AND CEN-PK genomes. (DOCX 26 kb)(.doc) Results of BLAST  List of parts used for transcriptional unit assembly. (DOCX 179 kb)Additional file 6: Figure S4.(.tiff) Mitochondrial fractionation from ATPA-NifU and MAM33-NifU cells. Lanes corresponding to total cell extract, pelleted cell debris after centrifugation, cytoplasmic and mitochondria-enriched fractions are shown. Anti-NifU WB is shown in the upper panel, anti-HSP60 WB  is the middle panel and anti-tubulin WB (cytoplasmic marker) is the lower panel. (PDF 677 kb)Additional file 7: Figure S5.(.doc) Addgene ID numbers of the plasmids described in this work. (DOCX 13 kb)