bioRxiv @biorxivpreprint@qoto.org

Available research on non-antibiotic alternative growth promoter (NAGPs) mainly focuses on the effect of a single preparation on the substitution effect of antibiotics. However, different NAGP might work together in harmony. Studies related to NAGP combinations are lacking. This study aimed to screen six non-antibiotic alternative growth promoter combinations (NAGPCs) in vitro so as to find a better alternative method to ensure feed efficiency and the broiler health. Pepsin and 42-d broiler ileal fluid were used for the in vitro digestion test, and the optimal addition levels of NAGPs and NAGPCs were selected based on dry matter (DM) and organic matter (OM) digestibility, microbiota of digestive fluid, and antioxidant capacity of digestive fluid. Results showed the optimum addition amount of Mannose oligosaccharide (MOS), fruit oligosaccharide (FOS), mannanase (MAN), Bacillus subtilis (BS), sodium butyrate (SB), guanidinoacetic acid (CA), xylanase (XYL), glucose oxidase (GO), and phytase (PT) were 0.2%, 0.9%, 0.03%, 0.05%, 0.08%, 0.002%, 0.008%, and 0.004%. The six best combinations were 0.2%MOS + 0.03%MAN + 0.15%SB, 0.2%MOS + 0.03%MAN + 0.05%BS, 0.2%MOS + 0.9%FOS + 0.15%SB, 0.2%MOS + 0.9%FOS + 0.05%BS, 0.2%MOS + 0.9%FOS + 0.03%MAN, and 0.2%MOS + 0.05%BS + 0.004%PT. In conclusion, NAGPCs improved the apparent digestibility of ileal DM and OM, intestinal flora and antioxidant capacity. Comparatively, under this condition, using NAGPC has more beneficial effects than using non-antibiotic alternative growth promoter. ### Competing Interest Statement The authors have declared no competing interest.

Field and Greenhouse studies that attempted to describe the molecular responses of trees under waterlogging (WL) combined with salinity (ST) are quasi-inexistent. To dissect plant-specific molecular responses and patterns under SWL, we integrated transcriptional and metabolic analyses involving common differentially expressed genes (DEGs) and metabolites (DMs) patterns in Dalbergia odorifera leaflets. SWL-treated seedlings exhibited an impressively high number of DEGs and DMs compared to ST or WL. Although the main common DEGs and DMs showed a neutral pattern, gene ontology enrichment following the classification in different functional categories of SWL-transcripts displayed a predominant synergistic pattern mode. Hierarchical and silhouette analysis regrouped different morpho-physiological clusters following the treatment, SWL was mainly grouped with both single stress. SWL induced a massive shutdown of the photosynthesis apparatus through LHCBs- and PSA-related genes. Starch and plastoglobuli synthesis appeared to be drastically affected by SWL, while ABA content confirmed by ABA synthesis-related genes (ABF, ABA1, and NCED) variations showed a less-needed role. NXN (Nucleoredoxin) genes are the main factors that sustain the antioxidant system under SWL. Here we provide the first molecular responses, characterization, and patterns of a tree under SWL that would significantly shed light on our understanding of the molecular mechanisms underlying combined stress.

Apigenin, a natural flavonoid, has shown early promise in colon cancer (CC); thus, exploring potential mechanisms of apigenin in CC is obligatory. In this study, shared targets of apigenin and CC were identified through different online tools and subjected to functional enrichment analyses like Gene Ontology and KEGG. Further, the protein-protein interaction network of the shared targets was developed (via STRING); hub/core targets were identified (MCODE application). The top targets of apigenin in CC were identified by molecular docking; further investigated for differential gene and protein expression in CC and their influence on CC patient survival (using TCGA data). Based on the docking score of the 13 hub genes, the top 3 targets (HSP90AA1, MMP9, PTGS2) were selected, and their expression was significantly elevated and related to poor overall survival in CC (except PTGS2). Molecular dynamics simulation further validated protein-ligand interactions and selected HSP90AA1 as the best target of apigenin in CC. Finally, apigenin was found to be involved in the cytotoxicity of CC cells (COLO-205) by reducing HSP90AA1 expression. The results of this study identified HSP90AA1 as one of the prime targets of apigenin in CC, and apigenin might act on HSP90AA1 to exert its anti-cancer mechanism. ### Competing Interest Statement The authors have declared no competing interest.

The Warburg Effect is characterized by accelerated glycolytic metabolism and lactate production and is a hallmark of cancer cells. Recently, we have demonstrated the role of endogenous, glucose-derived lactate as an oncometabolite which regulates gene expression in the estrogen receptor positive (ER+) MCF7 cell line cultivated in glucose media (San-Millan, Julian et al. 2019). Presently, with the addition of a triple negative breast cancer (TNBC) cell line, MDA-MB-231, we further confirm the effect of lactate on gene expression patterns, but extend results to include lactate effects on protein expression. As well, we report effects of lactate on the expression of E-cadherin and vimentin, proteins associated with epithelial-to-mesenchymal transition (EMT). Endogenous lactate regulates the expression of multiple genes involved in carcinogenesis. In MCF7 cells, lactate increased the expression of EGFR, VEGF HIF-1a, KRAS, MIF, mTOR, PIK3CA, TP53, and CDK4 (The Ital is used for genes) as well as decreased the expression of ATM, BRCA1, BRCA2, E2F1, MET, MYC, and RAF mainly at 48h of exposure. On the other hand, in the MDA-MB-231 cell line, lactate increased the expression of PIK3CA, VEGF, EGFR, mTOR, HIF-1α, ATM, E2F1, TP53 and decreased the expression of BRCA1, BRCA2, CDK4, CDK6, MET, MIF, MYC, and RAF after 48h of exposure. Protein expression of representative genes corroborated mRNA expressions. Finally, lactate decreased E-cadherin protein expression in MCF7 cells and increased vimentin expression in MDA-MB-231 cells. In this study, we demonstrate that endogenous lactate produced under aerobic conditions (Warburg Effect) is capable of eliciting important regulation of gene and protein expression in both ER+ and TNBC cell lines. The regulation of multiple genes by lactate is widespread and involves those involved in carcinogenesis including DNA repair, cell growth, proliferation, angiogenesis, and metastasis. Furthermore, both cell lines demonstrated changes in the expression of EMT biomarkers representing a shift to a more mesenchymal phenotype with exposure to endogenous lactate. ### Competing Interest Statement The authors have declared no competing interest.

Tumor-associated neutrophil (TAN) effects on glioblastoma biology remain under-characterized. We show here that 'hybrid' neutrophils with dendritic features - including morphological complexity, expression of antigen presentation genes, and the ability to process exogenous peptide and stimulate MHCII-dependent T cell activation - accumulate intratumorally and suppress tumor growth in vivo. Trajectory analysis of patient TAN scRNA-seq identifies this phenotype as a polarization state which is distinct from canonical cytotoxic TANs and differentiates intratumorally from immature precursors absent in circulation. Rather, these hybrid-inducible immature neutrophils - which we identified in patient and murine glioblastomas - arise from local skull marrow. Through labeled skull flap transplantation and targeted ablation, we characterize calvarial marrow as a potent contributor of antitumoral myeloid APCs, including hybrid TANs and dendritic cells, which elicit T cell cytotoxicity and memory. As such, agents augmenting neutrophil egress from skull marrow - such as intracalvarial AMD3100 whose survival prolonging-effect in GBM we demonstrate - present therapeutic potential. ### Competing Interest Statement The authors have declared no competing interest.

Microglial cells must act as the first line of defense of the central nervous system, but they can be exposed to various mechanical signals that may trigger their activation. While the impact of chemical signaling on brain cells has been studied in detail, our current understanding of the mechanical signaling in microglia is still limited. To address this challenge, we exposed microglial cells to a single mechanical stretch and compared their behavior to chemical activation by lipopolysaccharide treatment. Here we show that stretching microglial cells results in their activation, demonstrating a strong mechanosensitivity. Stretched microglial cells exhibited higher Iba1 protein levels, a denser actin cytoskeleton and migrated more persistently. In contrary to LPS-treated cells, stretched microglia maintain a robust secretory profile of chemokines and cytokines, except for TNF-α, highlighting the relevance of this model. Interestingly, a single stretch injury results in more compacted chromatin and DNA damage, suggesting possible long-term genomic instabilities in stretched microglia. Using neuronal networks in compartmentalized microfluidic chambers, we found that stretched microglial cells exhibit enhanced phagocytic and synaptic stripping activities. Altogether, our results propose that the immune potential of microglial cells can be unlocked by stretching events to maintain brain tissue homeostasis after mechanical injury. ### Competing Interest Statement The authors have declared no competing interest.

Living tissues are characterized by an intrinsically mechanochemical interplay of active physical forces and complex biochemical signalling pathways. Either feature alone can give rise to complex emergent phenomena, for example mechanically driven glassy dynamics and rigidity transitions, or chemically driven reaction-diffusion instabilities. An important question is how to quantitatively assess the contribution of these different cues to the large-scale dynamics of biological mate- rials. We address this in MDCK monolayers, considering both mechanochemical feedbacks between ERK signalling activity and cellular density as well as a mechanically active tissue rheology via a self-propelled vertex model. We show that the relative strength of active migration forces to mechanochemical couplings controls a transition from uniform active glass to periodic spatiotemporal waves. We parameterize the model from published experimental datasets on MDCK monolayers, and use it to make new predictions on the correlation functions of cellular dynamics and the dynamics of topological defects associated with the oscillatory phase of cells. Interestingly, MDCK monolayers are best described by an intermediary parameter region in which both mechanochemical couplings and noisy active propulsion have a strong influence on the dynamics. Finally, we study how tissue rheology and ERK waves feedback on one another, and uncover a mechanism via which tissue fluidity can be controlled by mechanochemical waves both at the local and global levels. ### Competing Interest Statement The authors have declared no competing interest.

The lung airways are characterized by long and wide proximal branches and short and thin distal branches. In this study, we investigated the emergence of this hierarchical structure through experimental observations and computational models. We focused on the branch formation in the pseudoglandular stage and examined the response of mouse lung epithelium to fibroblast growth factor 10 (FGF10) by monitoring extracellular signal-regulated kinase (ERK) activity. The ERK activity increased depending on the epithelial tissue curvature. This curvature-dependent response decreased as the development progressed. Therefore, to understand how these epithelial changes affect branching morphology, we constructed a computational model of curvature-dependent epithelial growth. We demonstrated that branch length was controlled by the curvature dependence of growth that was consistent with the experimental observations and lung morphology. However, the branching of the thin branches is suppressed in this model, which is inconsistent with the fact that thin branches in the lung are short. Thus, we introduced branch formation by apical constriction, which was shown to be regulated by Wnt signaling in our previous studies. Mathematical analysis indicated that the effect of apical constriction is cell shape-dependent, suggesting that apical constriction ameliorates the branching of thin branches. Finally, we were able to provide clarity on the hierarchical branching structure through an integrated computational model of curvature-dependent growth and cell shape regulation. We proposed that curvature-dependent growth involving FGF and Wnt-mediated cell shape regulation coordinate to control the spatial scale and frequency of branch formation. ### Competing Interest Statement The authors have declared no competing interest.

Single-molecule FRET (smFRET) is widely used to investigate dynamic (bio) molecular interactions taking place over distances of up to 10 nm. With the advent of recent super-resolution methods such as MINFLUX, MINSTED or RASTMIN, the spatiotemporal resolution of these techniques advanced towards the smFRET regime. While these methods do not suffer from the spatial restriction of FRET, they only visualize one emitter at a time, thus rendering fast dynamics of interactions out of reach. Here, we describe two approaches to overcome this limitation in pMINFLUX using its intrinsic fluorescence lifetime information. First, we combined pMINFLUX with smFRET. This enabled us to track a FRET donor fluorophore and simultaneously co-localize its FRET acceptor with nanometer precision. To extend co-localized tracking beyond the FRET range, we developed pMINFLUX lifetime multiplexing, a method to simultaneously track two fluorophores with similar spectral properties but distinct fluorescence lifetimes. We demonstrated its application on both static and dynamic DNA origami systems with a precision better than 2 nm. Within the FRET range, pMINFLUX lifetime multiplexing additionally uses a novel combined phasor-microtime-gating approach. This paves the way for nanometer precise co-localized tracking for inter-dye distances between 4 nm and 100 nm, closing the resolution gap between smFRET and co-tracking. ### Competing Interest Statement The authors have declared no competing interest.

The advances in high-throughput sequencing technology have led to significant progress in measuring gene expressions in single-cell level. The amount of publicly available single-cell RNA-seq (scRNA- seq) data is already surpassing 50M records for human with each record measuring 20,000 genes. This highlights the need for unsupervised representation learning to fully ingest these data, yet classical transformer architectures are prohibitive to train on such data in terms of both computation and memory. To address this challenge, we propose a novel asymmetric encoder-decoder transformer for scRNA-seq data, called xTrimoGene, which leverages the sparse characteristic of the data to scale up the pre-training. This scalable design of xTrimoGene reduces FLOPs by one to two orders of magnitude compared to classical transformers while maintaining high accuracy, enabling us to train the largest transformer models over the largest scRNA-seq dataset today. Our experiments also show that the performance of xTrimoGene improves as we increase the model sizes, and it also leads to SOTA performance over various downstream tasks, such as cell classification, perturb-seq effect prediction, and drug combination prediction. ### Competing Interest Statement The authors have declared no competing interest.

Ultrasound (US) muscle image series can be used for peripheral human-machine interfacing based on global features, or even on the decomposition of US images into the contributions of individual motor units (MUs). With respect to state-of-the-art surface electromyography (sEMG), US provides higher spatial resolution and deeper penetration depth. However, the accuracy of current methods for direct US decomposition, even at low forces, is relatively poor. These methods are based on linear mathematical models of the contributions of MUs to US images. Here, we test the hypothesis of linearity by comparing the average velocity twitch profiles of MUs when varying the number of other concomitantly active units. We observe that the velocity twitch profile has a decreasing peak-to-peak amplitude when tracking the same target motor unit at progressively increasing contraction force levels, thus with an increasing number of concomitantly active units. This observation indicates non-linear factors in the generation model. Furthermore, we directly studied the impact of one MU on a neighboring MU, finding that the effect of one source on the other is not symmetrical and may be related to unit size. We conclude that a linear approximation is limiting the decomposition methods to decompose full velocity twitch trains from velocity images, highlighting the need for more advanced models and methods for US decomposition than those currently employed. ### Competing Interest Statement The authors have declared no competing interest.

We introduce a novel framework BEATRICE to identify putative causal variants from GWAS summary statistics (https://github.com/sayangsep/Beatrice-Finemapping). Identifying causal variants is challenging due to their sparsity and to highly correlated variants in the nearby regions. To account for these challenges, our approach relies on a hierarchical Bayesian model that imposes a binary concrete prior on the set of causal variants. We derive a variational algorithm for this fine-mapping problem by minimizing the KL divergence between an approximate density and the posterior probability distribution of the causal configurations. Correspondingly, we use a deep neural network as an inference machine to estimate the parameters of our proposal distribution. Our stochastic optimization procedure allows us to simultaneously sample from the space of causal configurations. We use these samples to compute the posterior inclusion probabilities and determine credible sets for each causal variant. We conduct a detailed simulation study to quantify the performance of our framework across different numbers of causal variants and different noise paradigms, as defined by the relative genetic contributions of causal and non-causal variants. Using this simulated data, we perform a comparative analysis against two state-of-the-art baseline methods for fine-mapping. We demonstrate that BEATRICE achieves uniformly better coverage with comparable power and set sizes, and that the performance gain increases with the number of causal variants. Thus, BEATRICE is a valuable tool to identify causal variants from eQTL and GWAS summary statistics across complex diseases and traits. ### Competing Interest Statement The authors have declared no competing interest.

The Australian lungfish is a primitive and endangered representative of the subclass Dipnoi. The distribution of this species is limited to south-east Queensland, with some populations considered endemic and others possibly descending from translocations in the late nineteenth century shortly after European discovery. Attempts to resolve the historical distribution for this species have met with conflicting results based on descriptive genetic studies. Understanding if all populations are endemic or some are the result of, or influenced by, translocation events, has implications for conservation management. In this work, we analysed the genetic variation at three types of markers (mtDNA genomes, 11 STRs, and 5,196 nuclear SNPs) using the Approximate Bayesian Computation algorithm to compare several demographic models. We postulated different contributions of Mary River and Burnett River gene pools into the Brisbane River and North Pine River populations, related to documented translocation events. We ran the analysis for each marker separately, and we also estimated the posterior probabilities of the models combining the markers. Nuclear SNPs have the highest power to correctly identify the true model amongst the simulated datasets (where the model was known), but different markers typically provided similar answers. The most supported demographic model able to explain the real dataset implies that an endemic gene pool is present in the Brisbane and North Pine Rivers where past translocations are documented. These results will inform ongoing conservation efforts for this endangered and iconic species and warrant careful consideration of future genetic management of the Australian lungfish populations. ### Competing Interest Statement The authors have declared no competing interest.

A great many plants and animals have evolved separate sexes from hermaphroditism. In species with separate sexes, the development of an individual as male or female is often controlled by a diallelic sex-determining locus (XY and ZW systems). Transitions from hermaphroditism to separate sexes must therefore have often entailed the emergence of such a locus. However, the evolutionary mechanisms governing the emergence of XY and ZW systems in ancestral hermaphroditic populations, and in particular the mechanisms leading some species to acquire an XY rather than a ZW system, remain elusive. Here, we model the co-evolution of resource allocation to male and female functions (sex allocation) with the genetic architecture of sex determination, and show that gradual evolution readily leads to the emergence of XY and ZW systems. Our model also reveals a strong influence of the shape of the relationship between resource allocation and fecundity in each sex (male and female gain curves) on whether an XY or a ZW system evolves. This is because gain curves indicate the intensity of competition for reproduction through each sex, which in turn affects selection on the genetic architecture of sex allocation. Taken together, our results advance the understanding of sexual systems by uncovering a hitherto unappreciated link between the ecology and economics of sex allocation and the genetic basis of sex determination. ### Competing Interest Statement The authors have declared no competing interest.

Tropical tree reproductive phenology is sensitive to changing climate, but inter-individual and interannual variability at the regional scale is poorly understood. While large-scale and long-term datasets of environmental variables are available, reproductive phenology needs to be measured in-site, limiting the spatiotemporal scales of the data. We leveraged a unique dataset assembled by SeasonWatch, a citizen-science phenology monitoring programme in India to assess the environmental correlates of fruiting and flowering in three ubiquitous and economically important tree species - jackfruit, mango and tamarind - in the south-western Indian state of Kerala. Using 165006 observations spread over 19596 individual trees and over 9 years, and combined temperature and rainfall predictors for the fortnight preceding each observation, accessed using the ERA5-LAND dataset, we modelled the environmental correlates of reproductive phenophases - flower and fruit occurrence - in these species using two statistical approaches - machine learning and generalised linear mixed models. In these complementary approaches, we used a leave-one-year-out approach to cross-validate the model against observations. Models of phenophase presence for all species had higher predictive power than models of phenophase intensity. We found strong influences of multiple temperature and rainfall variables - soil moisture and maximum temperature had high importance values under machine learning models while the number of consecutive dry days also had high effect sizes in the generalised linear mixed models. The effect of time-varying environmental factors like total precipitation and consecutive dry days were also modified by the static predictors like elevation, aspect and urbanisation. Taken together, our results show the pervasive influence of climate on tropical tree reproductive phenology and extent of variability among years and individuals. We also demonstrate the potential and limitations of citizen-science observations in making and testing predictions at scale for predictive climate science in tropical landscapes. ### Competing Interest Statement The authors have declared no competing interest.

Research on the ultrastructural development of the kidney is limited, and research on rodent kidneys prevails. Yet, large differences between rodent and human nephrogenesis exist and therefore translation between species is not desirable. At the same time, there is an increasing demand for human research, in addition to assessing the potential of novel therapies such as renal organoids. We therefore generated an interactive atlas of large transmission electron microscopy tile scans of first trimester human kidneys, specifically Carnegie stage 20 until post-conceptional week 12. Analysis identified key ultrastructural features of proximal and distal progenitor cells such as cell shape, microvilli and luminal budding in the renal vesicle. Regarding glomerular development, we identified a new W-shaped body stage and three distinct sub-stages of the well-known capillary loop stage. Chromatin organization, nuclear shape and location were used to describe tubule cell identity and maturity, indicating a specific order of tubular maturation. The greatest congruence with adult tissue was seen in proximal tubules and the least in distal tubules. Finally, cytoplasmic glycogen depositions in collecting duct cells, which are absent in adult tissue, were found to be an early feature distinguishing distal tubules from collecting ducts as well as differentiating cortical from medullary collecting ducts. The findings of this research provide new fundamental insights for researchers who aim to understand and recreate kidney development. ### Competing Interest Statement The authors have declared no competing interest.

The Resistance-Nodulation-Division (RND) efflux pump superfamily is pervasive among Gram-negative pathogens and contributes extensively to clinical antibiotic resistance. The opportunistic pathogen Pseudomonas aeruginosa contains 12 RND-type efflux systems, with four contributing to resistance including MexXY-OprM which is uniquely able to export aminoglycosides. At the site of initial substrate recognition, small molecule probes of the inner membrane transporter (e.g., MexY) have potential as important functional tools to understand substrate selectivity and a foundation for developing adjuvant efflux pump inhibitors (EPIs). Here, we optimized the scaffold of berberine, a known but weak MexY EPI, using an in-silico high-throughput screen to identify berberine dimers with enhanced synergistic action with aminoglycosides. Further, docking and molecular dynamics simulations of berberine dimers reveal unique contact residues and thus sensitivities of MexY from distinct P. aeruginosa strains. This work thereby reveals berberine dimers to be useful probes of MexY transporter function and potential leads for EPI development. ### Competing Interest Statement The authors have declared no competing interest.

The bacterial DNA damage response is a critical, coordinated response to DNA replication stress. The canonical bacterial DNA damage response, first characterized in Escherichia coli, is controlled by the global transcriptional regulator LexA and the recombinase RecA. While genome-wide studies have described how the DNA damage response is regulated at a transcriptional level, relatively little is known about post-transcriptional regulation of this response. Here, we perform a proteome-wide survey of the DNA damage response in Caulobacter crescentus. We find that not all changes in protein abundance during the response to DNA damage are predicted by changes in transcription. We validate one of these post-transcriptionally regulated candidates to show its importance to survival of DNA damage. To investigate post-translational control of the DNA damage response, we perform a similar survey in cells lacking the Lon protease. This reveals that induction of the DNA damage response at the protein level is dampened in these strains, consistent with their reduced tolerance to DNA damage. Finally, proteome-wide stability measurements following damage nominate candidate Lon substrates that suggest post-translational regulation of the DNA damage response. The DNA damage response helps bacteria to respond to and potentially survive DNA damage. The mutagenesis that is induced as part of this response plays a role in bacterial evolution and is essential to the development and spread of antibiotic resistance. Understanding how bacteria coordinate their response to DNA damage could help us to combat this growing threat to human health. While the transcriptional regulation of the bacterial DNA damage response has been characterized, this study is the first to our knowledge to compare changes in RNA and protein levels to identify potential targets of post-transcriptional regulation in response to DNA damage. ### Competing Interest Statement The authors have declared no competing interest.

Bacterial chromosomes are dynamically and spatially organised within cells. In slow-growing Escherichia coli, the chromosomal terminus is initially located at the new pole and must therefore migrate to midcell during replication to reproduce the same pattern in the daughter cells. Here, we use high-throughput time-lapse microscopy to quantify this transition, its timing and its relationship to chromosome segregation. We find that terminus centralisation is a rapid discrete event that occurs ~25 min after initial separation of duplicated origins and ~50 min before the onset of bulk nucleoid segregation but with substantial variation between cells. Despite this variation, its movement is tightly coincident with the completion of origin segregation, even in the absence of its linkage to the divisome, suggesting a coupling between these two events. Indeed, we find that terminus centralisation does not occur if origin segregation away from mid-cell is disrupted, which results in daughter cells having an inverted chromosome organisation. Overall, our study quantifies the choreography of origin-terminus positioning and identifies an unexplored connection between these loci, furthering our understanding of chromosome segregation in this bacterium. ### Competing Interest Statement The authors have declared no competing interest.

Cancer cells exhibit dramatic differences in gene expression at the single-cell level which can predict whether they become resistant to treatment. Treatment perpetuates this heterogeneity, resulting in a diversity of cell states among resistant clones. However, it remains unclear whether these differences lead to distinct responses when another treatment is applied or the same treatment is continued. In this study, we combined single-cell RNA-sequencing with barcoding to track resistant clones through prolonged and sequential treatments. We found that cells within the same clone have similar gene expression states after multiple rounds of treatment. Moreover, we demonstrated that individual clones have distinct and differing fates, including growth, survival, or death, when subjected to a second treatment or when the first treatment is continued. By identifying gene expression states that predict clone survival, this work provides a foundation for selecting optimal therapies that target the most aggressive resistant clones within a tumor. ### Competing Interest Statement The authors have declared no competing interest.