METTL3 and N6-Methyladenosine Promote Homologous Recombination-Mediated Repair of DSBs by Modulating DNA-RNA Hybrid Accumulation.

Double-strand breaks (DSBs) are the most deleterious DNA lesions, which, if left unrepaired, may lead to genome instability or cell death. Here, we report that, in response to DSBs, the RNA methyltransferase METTL3 is activated by ATM-mediated phosphorylation at S43. Phosphorylated METTL3 is then localized to DNA damage sites, where it methylates the N6 position of adenosine (m6A) in DNA damage-associated RNAs, which recruits the m6A reader protein YTHDC1 for protection. In this way, the METTL3-m6A-YTHDC1 axis modulates accumulation of DNA-RNA hybrids at DSBs sites, which then recruit RAD51 and BRCA1 for homologous recombination (HR)-mediated repair. METTL3-deficient cells display defective HR, accumulation of unrepaired DSBs, and genome instability. Accordingly, depletion of METTL3 significantly enhances the sensitivity of cancer cells and murine xenografts to DNA damage-based therapy. These findings uncover the function of METTL3 and YTHDC1 in HR-mediated DSB repair, which may have implications for cancer therapy.

Genome-Wide Identification, Characterization, and Expression Profiling of AP2/ERF Superfamily Genes under Different Development and Abiotic Stress Conditions in Pecan (Carya illinoinensis).

The ethylene-responsive element (AP2/ERF) is one of the keys and conserved transcription factors (TFs) in plants that play a vital role in regulating plant growth, development, and stress response. A total of 202 AP2/ERF genes were identified from the pecan genome and renamed according to the chromosomal distribution of the CiAP2/ERF genes. They were divided into four subfamilies according to the domain and phylogenetic analysis, including 26 AP2, 168 ERF, six RAV, and two Soloist gene family members. These genes were distributed randomly across the 16 chromosomes, and we found 19 tandem and 146 segmental duplications which arose from ancient duplication events. The gene structure and conserved motif analysis demonstrated the conserved nature of intron/exon organization and motifs among the AP2/ERF genes. Several cis-regulatory elements, which were related to light responsiveness, stress, and defense responses, were identified in the promoter regions of AP2/ERFs. The expression profiling of 202 CiAP2/ERF genes was assessed by using RNA-Seq data and qRT-PCR during development (pistillate flowering development, graft union development, and kernel development) and under abiotic stresses (waterlogging, drought). Moreover, the results suggested that the ERF-VII members may play a critical role in waterlogging stress. These findings provided new insights into AP2/ERF gene evolution and divergence in pecan and can be considered a valuable resource for further functional validation, as well as for utilization in a stress-resistance-variety development program.

Novel immune-related signature for risk stratification and prognosis in prostatic adenocarcinoma.

A substantial proportion of prostatic adenocarcinoma (PRAD) patients experience biochemical failure (BCF) after radical prostatectomy (RP). The immune microenvironment plays a vital role in carcinogenesis and the development of PRAD. This study aimed to identify a novel immune-related gene (IRG)-based signature for risk stratification and prognosis of BCF in PRAD. Weighted gene coexpression network analysis was carried out to identify a BCF-related module in a discovery cohort of patients who underwent RP at the Massachusetts General Hospital. The median follow-up time was 70.32 months. Random forest and multivariate stepwise Cox regression analyses were used to identify an IRG-based signature from the specific module. Risk plot analyses, Kaplan-Meier curves, receiver operating characteristic curves, univariate and multivariate Cox regression analyses, stratified analysis, and Harrell's concordance index were used to assess the prognostic value and predictive accuracy of the IRG-based signature in the internal discovery cohort; The Cancer Genome Atlas database was used as a validation cohort. Tumor immune estimation resource database analysis and CIBERSORT algorithm were used to assess the immunophenotype of PRAD. A novel IRG-based signature was identified from the specific module. Five IRGs (BUB1B, NDN, NID1, COL4A6, and FLRT2) were verified as components of the risk signature. The IRG-based signature showed good prognostic value and predictive accuracy in both the discovery and validation cohorts. Infiltrations of various immune cells were significantly different between low-risk and high-risk groups in PRAD. We identified a novel IRG-based signature that could function as an index for assessing tumor immune status and risk stratification in PRAD.

[Bioinformatics-based identification of the key genes associated with prostate cancer].

OBJECTIVE: To identify the key genes associated with the pathogenesis of PCa using the bioinformatics approach for a deeper insight into the molecular mechanisms underlying the development and progression of PCa. METHODS: The microarray datasets GSE70770, GSE32571 and GSE46602 were downloaded from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEG) in the normal prostate tissue and PCa were identified with the GEO2R tool, followed by functional enrichment analysis. A protein-protein interaction (PPI) network of DEGs was constructed by STRING and visualized with the Cytoscape software. RESULTS: A total of 235 DEGs were identified, including 61 up-regulated and 174 down-regulated genes, which were mainly enriched in focal adhesion kinase (FAK), ECM-receptor interaction, and other signaling pathways. From the PPI network were screened out 12 highly connected hub genes, including MYH11, TPM1, TPM2, SMTN, MYL9, VCL, ACTG1, CNN1, CALD1, ACTC1, MYLK and SORBS1, which were shown by hierarchical cluster analysis to be capable of distinguishing prostate cancer from non-cancer tissue. CONCLUSIONS: A total of 235 DEGs and 12 hub genes were identified in this study, which may contribute to a further understanding of the molecular mechanisms of the development and progression of PCa, and provide new candidate targets for the diagnosis and treatment of the malignancy.

[Effective medicinal ingredients and screening of excellent germplasm in Rubus chingii].

In order to provide rationale for selection of good germplasm in Rubus chingii, main effective medicinal ingredients of green fruit such as gallic acid, ellagic acid, kaempferol-3-rutinoside, astragalin and tiliroside were measured using UPLC for the samples collected from Chun'an county of Zhejiang province, and such parameters as soluble solid contents of ripe fruit of some samples were also measured to study variation among individuals and correlation. It has been found that there were differences among individuals in the contents of gallic acid, ellagic acid, kaempferol-3-rutinoside, astragalin and tiliroside, which ranged from 0.010 2%-0.027 4%, 0.089 5%-0.291 1%, 0.010 5%-0.114 8%, 0.005 8%-0.041 2% and 0.010 9%-0.086 3%, respectively, with a CV of 18.60%, 27.02%, 44.23%, 44.17% and 47.29%, respectively. Gallic acid was positively correlated with ellagic acid, but negatively with kaempferol-3-rutinoside and astragalin significantly. Significantly positive correlation existed between kaempferol-3-rutinoside, astragalin and linden glycoside as well as between ellagic acid and fruit shape index of ripe fruit and between linden glycoside and the content of soluble solids. 51.35% of the individuals had a content of soluble solids more than 15%. Therefore, abundant variations have been found among individuals in effective medicinal ingredients in R. chingii, which shows great potential for selection, but only do 7.61% of the individuals meet the requirement of Chinese pharmacopoeia in terms of the contents of effective medicinal ingredients. Therefore, selection could be first performed in terms of fruit shape index of ripe red fruit, followed by the contents of ellagic acid and kaempferol-3-rutinoside measured. The individuals, in which the contents of effective medicinal ingredients don't meet the requirement of Chinese pharmacopoeia, could be considered for the selection in terms of edible fresh fruit.

A unified DNA sequence and non-DNA sequence mapping model of complex traits.

Increasing evidence shows that quantitative inheritance is based on both DNA sequence and non-DNA sequence variants. However, how to simultaneously detect these variants from a mapping study has been unexplored, hampering our effort to illustrate the detailed genetic architecture of complex traits. We address this issue by developing a unified model of quantitative trait locus (QTL) mapping based on an open-pollinated design composed of randomly sampling maternal plants from a natural population and their half-sib seeds. This design forms a two-level hierarchical platform for a joint linkage-linkage disequilibrium analysis of population structure. The EM algorithm was implemented to estimate and test DNA sequence-based effects and non-DNA sequence-based effects of QTLs. We applied this model to analyze genetic mapping data from the OP design of a gymnosperm coniferous species, Torreya grandis, identifying 25 significant DNA sequence and non-DNA sequence QTLs for seedling height and diameter growth in different years. Results from computer simulation show that the unified model has good statistical properties and is powerful for QTL detection. Our model enables the tests of how a complex trait is affected differently by DNA-based effects and non-DNA sequence-based transgenerational effects, thus allowing a more comprehensive picture of genetic architecture to be charted and quantified.

Increased expression of immediate early response gene 3 protein promotes aggressive progression and predicts poor prognosis in human bladder cancer.

BACKGROUND: Immediate early response gene 3 (IER3) is a stress-inducible gene, which exerts diverse effects in regulating cell apoptosis and cell cycle. Growing evidence shows that IER3 functions either as an oncogene or a tumor suppressor in various human cancers with a cancer type-dependent manner. However, the involvement of IER3 in human bladder cancer (BCa) has not been elucidated. In the current study, we aimed to investigate the expression pattern and the clinical significance of IER3 in BCa. METHODS: We performed immunohistochemistry analysis to examine the subcellular localization and the expression levels of IER3 protein in 88 BCa specimens obtained from Department of Pathology in Massachusetts General Hospital. The associations of IER3 protein expression with various clinicopathological features and patients' overall survival were statistically evaluated. RESULTS: IER3 protein was mainly expressed in the cytoplasm in bladder cancer cell. Of 88 BCa tissue specimens, 39 (44.3%) showed high expression of IER3 protein and 49 (55.7%) showed low expression. High IER3 protein expression was significantly associated with high pathologic nodal stage (p = 0.018). Kaplan-Meier analysis revealed that the overall survival of BCa patients with overexpression of IER3 protein was shorter than that with low expression (p < 0.01). Multivariate analysis by Cox regression further identified IER3 as an independent prognostic factor of BCa patients (p = 0.010). CONCLUSIONS: Our findings suggest for the first time that the increased expression of IER3 protein may promote the aggressive progression of BCa. Importantly, IER3 may be a potential prognostic marker for BCa patients.

A statistical design for testing apomictic diversification through linkage analysis.

The capacity of apomixis to generate maternal clones through seed reproduction has made it a useful characteristic for the fixation of heterosis in plant breeding. It has been observed that apomixis displays pronounced intra- and interspecific diversification, but the genetic mechanisms underlying this diversification remains elusive, obstructing the exploitation of this phenomenon in practical breeding programs. By capitalizing on molecular information in mapping populations, we describe and assess a statistical design that deploys linkage analysis to estimate and test the pattern and extent of apomictic differences at various levels from genotypes to species. The design is based on two reciprocal crosses between two individuals each chosen from a hermaphrodite or monoecious species. A multinomial distribution likelihood is constructed by combining marker information from two crosses. The EM algorithm is implemented to estimate the rate of apomixis and test its difference between two plant populations or species as the parents. The design is validated by computer simulation. A real data analysis of two reciprocal crosses between hickory (Carya cathayensis) and pecan (C. illinoensis) demonstrates the utilization and usefulness of the design in practice. The design provides a tool to address fundamental and applied questions related to the evolution and breeding of apomixis.

A reciprocal cross design to map the genetic architecture of complex traits in apomictic plants.

Many higher plants of economic and biological importance undergo apomixis in which the maternal tissue of the ovule forms a seed, without experiencing meiosis and fertilization. This feature of apomixis has made it difficult to perform linkage mapping which relies on meiotic recombination. Here, we describe a computational model for mapping quantitative trait loci (QTLs) that control complex traits in apomictic plants. The model is founded on the mixture model-based likelihood in which maternal genotypes are dissolved into two possible components generated by meiotic and apomictic processes, respectively. The EM algorithm was implemented to discern meiotic and apomictic genotypes and, therefore, allow the marker-QTL linkage relationship to be estimated. By capitalizing on reciprocal crosses, the model is renovated to estimate and test imprinting effects of QTLs, providing a better gateway to characterize the genetic architecture of complex traits. The model was validated through computer simulation and further demonstrated for its usefulness by analyzing a real data for an apomictic woody plant. The model has for the first time provided a unique tool for genetic mapping in apomictic plants.

Overexpression of NIMA-related kinase 2 is associated with progression and poor prognosis of prostate cancer.

BACKGROUND: The NIMA-related kinase 2 (NEK2) is a serine/threonine kinase that is involved in regulation of centrosome duplication and spindle assembly during mitosis. Dysregulation of these processes causes chromosome instability and aneuploidy, which are hallmark changes of many solid tumors. However, whether aberrant expression of NEK2 is associated with outcome of prostate cancer (PCa) patients remains to be determined. METHODS: Expression of NEK2 in human PCa cells and primary PCa tissues was assessed by quantitative RT-PCR. Expression of NEK2 in human PCa cells was depleted with siRNA. Effects of the depletion on cell proliferation, survival, and tumorigenicity were assessed both in vitro with cell cultures and in vivo with subcutaneous implantation of xenografts. In silico analyses of the online Taylor dataset were carried out to determine whether the expression level of NEK2 correlated with the clinicopathological characteristics of prostate cancer. RESULTS: Compared with benign human prostatic epithelial cells and tissues, the expression of NEK2 was elevated in human PCa cells and primary PCa tissues. Depleting NEK2 expression inhibited human PCa cell proliferation in vitro and xenograft growth in vivo. Expression level of NEK2 in PCa positively correlated with the Gleason score and pathologic stage of the patient. CONCLUSION: The results suggest that overexpression of NEK2 has the potential to serve as a biomarker for PCa prognosis. Further validation with large sample pool is warrant.

Genetic linkage map construction and QTL identification of juvenile growth traits in Torreya grandis.

Torreya grandis Fort. ex Lindl, a conifer species widely distributed in Southeastern China, is of high economic value by producing edible, nutrient seeds. However, knowledge about the genome structure and organization of this species is poorly understood, thereby limiting the effective use of its gene resources. Here, we report on a first genetic linkage map for Torreya grandis using 96 progeny randomly chosen from a half-sib family of a commercially cultivated variety of this species, Torreya grandis Fort. ex Lindl cv. Merrillii. The map contains 262 molecular markers, i.e., 75 random amplified polymorphic DNAs (RAPD), 119 inter-simple sequence repeats (ISSR) and 62 amplified fragments length polymorphisms (AFLP), and spans a total of 7,139.9 cM, separated by 10 linkage groups. The linkage map was used to map quantitative trait loci (QTLs) associated with juvenile growth traits by functional mapping. We identified four basal diameter-related QTLs on linkage groups 1, 5 and 9; four height-related QTLs on linkage groups 1, 2, 5 and 8. It was observed that the genetic effects of QTLs on growth traits vary with age, suggesting the dynamic behavior of growth QTLs. Part of the QTLs was found to display a pleiotropic effect on basal diameter growth and height growth.

Development of SSR Markers in Hickory (Carya cathayensis Sarg.) and Their Transferability to Other Species of Carya.

Hickory (Carya cathayensis Sarg.), an important nut-producing species in Southeastern China, has high economic value, but so far there has been no cultivar bred under species although it is mostly propagated by seeding and some elite individuals have been found. It has been found recently that this species has a certain rate of apomixis and poor knowledge of its genetic background has influenced development of a feasible breeding strategy. Here in this paper we first release SSR (Simple sequence repeat) markers developed in this species and their transferability to other three species of the same genus, Carya. A total of 311 pairs of SSR primers in hickory were developed based on sequenced cDNAs of a fruit development-associated cDNA library and RNA-seq data of developing female floral buds and could be used to distinguish hickory, C. hunanensis Cheng et R. H. Chang ex R. H. Chang et Lu, C. illinoensis K. Koch (pecan) and C. dabieshanensis M. C. Liu et Z. J. Li, but they were monomorphic in both hickory and C. hunanensis although multi-alleles have been identified in all the four species. There is a transferability rate of 63.02% observed between hickory and pecan and the markers can be applied to study genetic diversity of accessions in pecan. When used in C. dabieshanensis, it was revealed that C. dabieshanensis had the number of alleles per locus ranging from 2 to 4, observed heterozygosity from 0 to 0.6667 and expected heterozygosity from 0.333 to 0.8667, respectively, which supports the existence of C. dabieshanensis as a separate species different from hickory and indicates that there is potential for selection and breeding in this species.

VSOLassoBag: a variable-selection oriented LASSO bagging algorithm for biomarker discovery in omic-based translational research.

Screening biomolecular markers from high-dimensional biological data is one of the long-standing tasks for biomedical translational research. With its advantages in both feature shrinkage and biological interpretability, Least Absolute Shrinkage and Selection Operator (LASSO) algorithm is one of the most popular methods for the scenarios of clinical biomarker development. However, in practice, applying LASSO on omics-based data with high dimensions and low-sample size may usually result in an excess number of predictive variables, leading to the overfitting of the model. Here, we present VSOLassoBag, a wrapped LASSO approach by integrating an ensemble learning strategy to help select efficient and stable variables with high confidence from omics-based data. Using a bagging strategy in combination with a parametric method or inflection point search method, VSOLassoBag can integrate and vote variables generated from multiple LASSO models to determine the optimal candidates. The application of VSOLassoBag on both simulation datasets and real-world datasets shows that the algorithm can effectively identify markers for either case-control binary classification or prognosis prediction. In addition, by comparing with multiple existing algorithms, VSOLassoBag shows a comparable performance under different scenarios while resulting in fewer features than others. In summary, VSOLassoBag, which is available at https://seqworld.com/VSOLassoBag/ under the GPL v3 license, provides an alternative strategy for selecting reliable biomarkers from high-dimensional omics data. For user's convenience, we implement VSOLassoBag as an R package that provides multithreading computing configurations.

The Genetic Architecture of Juvenile Growth Traits in the Conifer Torreya grandis as Revealed by Joint Linkage and Linkage Disequilibrium Mapping.

Despite its high economical and ornamental values, Torreya grandis, a dioecious non-timber coniferous species, has long been an underrepresented species. However, the advent and application of advanced genotyping technologies have stimulated its genetic research, making it possible to gain new insight into the genetic architecture of complex traits that may not be detected for model species. We apply an open-pollination (OP) mapping strategy to conduct a QTL mapping experiment of T. grandis, in which nearly 100 unrelated trees randomly chosen from the species' natural distribution and their half-sib progeny are simultaneously genotyped. This strategy allows us to simultaneously estimate the recombination fractions and linkage disequilibrium (LD) coefficients between each pair of markers. We reconstruct a high-density linkage map of 4,203 SNPs covering a total distance of 8,393.95 cM and plot pairwise normalized LD values against genetic distances to build up a linkage-LD map. We identify 13 QTLs for stem basal diameter growth and 4 QTLs for stem height growth in juvenile seedlings. From the linkage-LD map, we infer the evolutionary history of T. grandis and each of its QTLs. The slow decay of QTL-related LDs indicates that these QTLs and their harboring genomic regions are evolutionarily relatively young, suggesting that they can better utilized by clonal propagation rather than through seed propagation. Genetic results from the OP sampling strategy could provide useful guidance for genetic studies of other dioecious species.

Electroacupuncture attenuates surgical pain-induced delirium-like behavior in mice via remodeling gut microbiota and dendritic spine.

Surgical pain is associated with delirium in patients, and acupuncture can treat pain. However, whether electroacupuncture can attenuate the surgical pain-associated delirium via the gut-brain axis remains unknown. Leveraging a mouse model of foot incision-induced surgical pain and delirium-like behavior, we found that electroacupuncture stimulation at specific acupoints (e.g., DU20+KI1) attenuated both surgical pain and delirium-like behavior in mice. Mechanistically, mice with incision-induced surgical pain and delirium-like behavior showed gut microbiota imbalance, microglia activation in the spinal cord, somatosensory cortex, and hippocampus, as well as an enhanced dendritic spine elimination in cortex revealed by two-photon imaging. The electroacupuncture regimen that alleviated surgical pain and delirium-like behavior in mice also effectively restored the gut microbiota balance, prevented the microglia activation, and reversed the dendritic spine elimination. These data demonstrated a potentially important gut-brain interactive mechanism underlying the surgical pain-induced delirium in mice. Pending further studies, these findings revealed a possible therapeutic approach in preventing and/or treating postoperative delirium by using perioperative electroacupuncture stimulation in patients.

A model for linkage analysis with apomixis.

Apomixis, or asexual reproduction through seeds, occurs in over 400 species of angiosperms. Although apomixis can favorably perpetuate desired genotypes through successive seed generation, it may also bring about some difficulty for linkage analysis and quantitative trait locus mapping. In this article, we explore the issue of how apomixis affects the precision and power of linkage analysis with molecular markers. We derive a statistical model for estimating the linkage between different markers when some progeny are derived from apomixis. The model was constructed within the maximum likelihood framework and implemented with the EM algorithm. A series of procedures are formulated to test the linkage of markers, the rate of apomixis, and the degree of genetic interference during meiosis. The model was examined and validated through simulation studies. The model will provide a tool for linkage mapping and evolutionary studies for plant species that undergo apomixis.

RBMX is required for activation of ATR on repetitive DNAs to maintain genome stability.

ATR is a master regulator of cell response to replication stress. Adequate activation of ATR is essential for preventing genome aberrance induced by replication defect. However, the mechanism underlying ATR activation is not fully understood. Here, we identify that RBMX is an ssDNA binding protein that orchestrates a novel pathway to activate ATR. Using super-resolution STORM, we observe that RBMX and RPA bind to adjacent but nonoverlapping sites on ssDNA in response to replication stress. RBMX then binds to and facilitates positioning of TopBP1, which activates nearby ATR associated with RPA. In addition, ATR activation by ssDNA-RBMX-TopBP1 is independent of ssDNA-dsDNA junction and 9-1-1 complex. ChIP-seq analysis reveals that RBMX/RPA are highly enriched on repetitive DNAs, which are considered as fragile sites with high replication stress. RBMX depletion leads to defective localization of TopBP1 to replication stressed sites and inadequate activation of ATR. Furthermore, cells with deficient RBMX demonstrate replication defect, leading to formation of micronuclei and a high rate of sister-chromatin exchange, indicative of genome instability. Together, the results identify a new ssDNA-RBMX-TopBP1 pathway that is specifically required for activation of ATR on repetitive DNAs. Therefore, RBMX is a key factor to ensure genome stability during replication.

Genetic mapping of developmental instability: design, model and algorithm.

Developmental instability or noise, defined as the phenotypic imprecision of an organism in the face of internal or external stochastic disturbances, has been thought to play an important role in shaping evolutionary processes and patterns. The genetic studies of developmental instability have been based on fluctuating asymmetry (FA) that measures random differences between the left and the right sides of bilateral traits. In this article, we frame an experimental design characterized by a spatial autocorrelation structure for determining the genetic control of developmental instability for those traits that cannot be bilaterally measured. This design allows the residual environmental variance of a quantitative trait to be dissolved into two components due to permanent and random environmental factors. The degree of developmental instability is quantified by the relative proportion of the random residual variance to the total residual variance. We formulate a mixture model to estimate and test the genetic effects of quantitative trait loci (QTL) on the developmental instability of the trait. The genetic parameters including the QTL position, the QTL effects, and spatial autocorrelations are estimated by implementing the EM algorithm within the mixture model framework. Simulation studies were performed to investigate the statistical behavior of the model. A live example for poplar trees was used to map the QTL that control root length growth and its developmental instability from cuttings in water culture.

Estimation of multilocus linkage disequilibria in diploid populations with dominant markers.

Analysis of population structure and organization with DNA-based markers can provide important information regarding the history and evolution of a species. Linkage disequilibrium (LD) analysis based on allelic associations between different loci is emerging as a viable tool to unravel the genetic basis of population differentiation. In this article, we derive the EM algorithm to obtain the maximum-likelihood estimates of the linkage disequilibria between dominant markers, to study the patterns of genetic diversity for a diploid species. The algorithm was expanded to estimate and test linkage disequilibria of different orders among three dominant markers and can be technically extended to manipulate an arbitrary number of dominant markers. The feasibility of the proposed algorithm is validated by an example of population genetic studies of hickory trees, native to southeastern China, using dominant random amplified polymorphic DNA markers. Extensive simulation studies were performed to investigate the statistical properties of this algorithm. The precision of the estimates of linkage disequilibrium between dominant markers was compared with that between codominant markers. Results from simulation studies suggest that three-locus LD analysis displays increased power of LD detection relative to two-locus LD analysis. This algorithm is useful for studying the pattern and amount of genetic variation within and among populations.

Mathematical model to appraise the inhibitory effect of phenolic compounds derived from lignin for biobutanol production.

This study aimed to establish a mathematical modeling to evaluate the inhibitory effect of phenolic derivatives on acetone-butanol-ethanol (ABE) fermentation by Clostridium saccharoperbutylacetonicum N1-4. Vanillin, 4-hydroxybenzoic acid, and syringaldehyde were selected to represent guaiacyl, hydroxyphenyl, and syringyl phenols, respectively, to be examined in a series of fed-batch experiments. Results show the presence of phenolic derivatives blocked the pathway of the assimilation of organic acids and reduced cell growth and glucose utilization. The inhibition model projected that the levels of 0.13, 0.14, and 0.04 g L-1 for vanillin, 4-hydroxybenzoic acid, and syringaldehyde, respectively, resulted in 25% inhibition of butanol production, whereas 100% inhibition was predicted at the levels of 4.94, 4.37, and 4.20 g L-1 for vanillin, 4-hydroxybenzoic acid, and syringaldehyde, respectively. Syringaldehyde was more toxic than the other two compounds. The established model described that the phenolic compounds derived from different phenyl propane monomers of lignin severely obstructed biobutanol production.