Cold Influences Male Reproductive Development in Plants: A Hazard to Fertility, but a Window for Evolution.

Being sessile organisms, plants suffer from various abiotic stresses including low temperature. In particular, male reproductive development of plants is extremely sensitive to cold which may dramatically reduce viable pollen shed and plant fertility. Cold stress disrupts stamen development and prominently interferes with the tapetum, with the stress-responsive hormones ABA and gibberellic acid being greatly involved. In particular, low temperature stress delays and/or inhibits programmed cell death of the tapetal cells which consequently damages pollen development and causes male sterility. On the other hand, studies in Arabidopsis and crops have revealed that ectopically decreased temperature has an impact on recombination and cytokinesis during meiotic cell division, implying a putative role for temperature in manipulating plant genomic diversity and architecture during the evolution of plants. Here, we review the current understanding of the physiological impact of cold stress on the main male reproductive development processes including tapetum development, male meiosis and gametogenesis. Moreover, we provide insights into the genetic factors and signaling pathways that are involved, with putative mechanisms being discussed.

Mutational Mtc6p attenuates autophagy and improves secretory expression of heterologous proteins in Kluyveromyces marxianus.

BACKGROUND: The yeast Kluyveromyces marxianus is an emerging cell factory for heterologous protein biosynthesis and its use holds tremendous advantages for multiple applications. However, which genes influence the productivity of desired proteins in K. marxianus has so far been investigated by very few studies. RESULTS: In this study, we constructed a K. marxianus recombinant (FIM1/Est1E), which expressed the heterologous ruminal feruloyl esterase Est1E as reporter. UV-60Co-γ irradiation mutagenesis was performed on this recombinant, and one mutant (be termed as T1) was screened and reported, in which the productivity of heterologous Est1E was increased by at least tenfold compared to the parental FIM1/Est1E recombinant. Transcriptional perturbance was profiled and presented that the intracellular vesicle trafficking was enhanced while autophagy be weakened in the T1 mutant. Moreover, whole-genome sequencing combined with CRISPR/Cas9 mediated gene-editing identified a novel functional protein Mtc6p, which was prematurely terminated at Tyr251 by deletion of a single cytosine at 755 loci of its ORF in the T1 mutant. We found that deleting C755 of MTC6 in FIM1 led to 4.86-fold increase in the production of Est1E compared to FIM1, while the autophagy level decreased by 47%; on the contrary, when reinstating C755 of MTC6 in the T1 mutant, the production of Est1E decreased by 66% compared to T1, while the autophagy level increased by 124%. Additionally, in the recombinant with attenuated autophagy (i.e., FIM1 mtc6C755Δ and T1) or interdicted autophagy (i.e., FIM1 atg1Δ and T1 atg1Δ), the productivity of three other heterologous proteins was also increased, specifically the heterologous mannase Man330, the ß-1,4-endoxylanase XynCDBFV or the conventional EGFP. CONCLUSIONS: Our results demonstrated that Mtc6p was involved in regulating autophagy; attenuating or interdicting autophagy would dramatically improve the yields of desired proteins in K. marxianus, and this modulation could be achieved by focusing on the premature mutation of Mtc6p target.

Downregulation of selenium-binding protein 1 is associated with poor prognosis in lung squamous cell carcinoma.

BACKGROUND: We found that selenium-binding protein 1 (SBP1) was progressively decreased in the human bronchial epithelial carcinogenic processes. Knockdown of SBP1 in immortalized human bronchial epithelial cell line 16HBE cells significantly increased the efficiency of B[a]P-induced cell transformation. However, the relationship between SBP1 expression and clinicopathological factors of patients has not been defined completely. The specific role of SBP1 in prognosis of lung squamous cell carcinoma (LSCC) is still unknown. METHODS: Tissue samples from 82 patients treated by pulmonary lobectomy for LSCC were used. Immunohistochemistry and western blotting were used to detect the expressions of SBP1 protein. The relationships between the expression level of SBP1 and the clinicopathological features of patients were analyzed. Cox proportional hazard regression analysis and Kaplan-Meier method were used to perform survival analysis. RESULTS: Expressions of SBP1 proteins were significantly lower in LSCC tissues than that in the corresponding normal bronchial epithelium (NBE) tissues (P = 0.000). In LSCC, The expression levels of SBP1 had not correlated with patients' age, gender, smoking state, primary tumor stages (T), TNM clinical stages, and distant metastasis (M) (P > 0.05). However, downregulation of SBP1 was significantly associated with higher lymph node metastasis and lower overall survival rate (P < 0.05). Cox regression analysis indicated low expressions of SBP1 can be an independent prognostic factor for poor overall survival in LSCC patients (P = 0.002). CONCLUSIONS: Downregulation of SBP1 may play a key role in the tumorigenic process of LSCC. SBP1 may be a novel potential prognostic factor of LSCC.

A stochastic model for identifying differential gene pair co-expression patterns in prostate cancer progression.

BACKGROUND: The identification of gene differential co-expression patterns between cancer stages is a newly developing method to reveal the underlying molecular mechanisms of carcinogenesis. Most researches of this subject lack an algorithm useful for performing a statistical significance assessment involving cancer progression. Lacking this specific algorithm is apparently absent in identifying precise gene pairs correlating to cancer progression. RESULTS: In this investigation we studied gene pair co-expression change by using a stochastic process model for approximating the underlying dynamic procedure of the co-expression change during cancer progression. Also, we presented a novel analytical method named 'Stochastic process model for Identifying differentially co-expressed Gene pair' (SIG method). This method has been applied to two well known prostate cancer data sets: hormone sensitive versus hormone resistant, and healthy versus cancerous. From these data sets, 428,582 gene pairs and 303,992 gene pairs were identified respectively. Afterwards, we used two different current statistical methods to the same data sets, which were developed to identify gene pair differential co-expression and did not consider cancer progression in algorithm. We then compared these results from three different perspectives: progression analysis, gene pair identification effectiveness analysis, and pathway enrichment analysis. Statistical methods were used to quantify the quality and performance of these different perspectives. They included: Re-identification Scale (RS) and Progression Score (PS) in progression analysis, True Positive Rate (TPR) in gene pair analysis, and Pathway Enrichment Score (PES) in pathway analysis. Our results show small values of RS and large values of PS, TPR, and PES; thus, suggesting that gene pairs identified by the SIG method are highly correlated with cancer progression, and highly enriched in disease-specific pathways. From this research, several gene interaction networks inferred could provide clues for the mechanism of prostate cancer progression. CONCLUSION: The SIG method reliably identifies cancer progression correlated gene pairs, and performs well both in gene pair ontology analysis and in pathway enrichment analysis. This method provides an effective means of understanding the molecular mechanism of carcinogenesis by appropriately tracking down the process of cancer progression.