Plants are extensively used in traditional medicine, and several plant antimicrobial peptides have been described as potential alternatives to conventional antibiotics. However, after more than four decades of research no plant antimicrobial peptide is currently used for treating bacterial infections, due to their length, post-translational modifications or  high dose requirement for a therapeutic effect . Here we report the design of antimicrobial peptides derived from a guava glycine-rich peptide using a genetic algorithm. This approach yields guavanin peptides, arginine-rich α-helical peptides that possess an unusual hydrophobic counterpart mainly composed of tyrosine residues. Guavanin 2 is characterized as a prototype peptide in terms of structure and activity. Nuclear magnetic resonance analysis indicates that the peptide adopts an α-helical structure in hydrophobic environments. Guavanin 2 is bactericidal at low concentrations, causing membrane disruption and triggering hyperpolarization. This computational approach for the exploration of natural products could be used to design effective peptide antibiotics.

Cationic antimicrobial peptides (AMPs) and host defense peptides (HDPs) show vast potential as peptide-based drugs. Great effort has been made in order to exploit their mechanisms of action, aiming to identify their targets as well as to enhance their activity and bioavailability. In this review, we will focus on both naturally occurring and designed antiviral and antitumor cationic peptides, including those here called promiscuous, in which multiple targets are associated with a single peptide structure. Emphasis will be given to their biochemical features, selectivity against extra targets, and molecular mechanisms. Peptides which possess antitumor activity against different cancer cell lines will be discussed, as well as peptides which inhibit virus replication, focusing on their applications for human health, animal health and agriculture, and their potential as new therapeutic drugs. Moreover, the current scenario for production and the use of nanotechnology as delivery tool for both classes of cationic peptides, as well as the perspectives on improving them is considered.

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BackgroundSoybean pathogens and pests reduce grain production worldwide. Biotic interaction cause extensive changes in plant gene expression profile and the data produced by functional genomics studies need validation, usually done by quantitative PCR. Nevertheless, this technique relies on accurate normalization which, in turn, depends upon the proper selection of stable reference genes for each experimental condition. To date, only a few studies were performed to validate reference genes in soybean subjected to biotic stress. Here, we report reference genes validation in soybean during root-knot nematode (Meloidogyne incognita) parasitism and velvetbean caterpillar (Anticarsia gemmatalis) attack.FindingsThe expression stability of nine classical reference genes (GmCYP2, GmELF1A, GmELF1B, GmACT11, GmTUB, GmTUA5, GmG6PD, GmUBC2 and GmUBC4) was evaluated using twenty-four experimental samples including different organs, developmental stages, roots infected with M. incognita and leaves attacked by A. gemmatalis. Two different algorithms (geNorm and NormFinder) were used to determine expression stability. GmCYP2 and GmUBC4 are the most stable in different organs. Considering the developmental stages, GmELF1A and GmELF1B genes are the most stable. For spatial and temporal gene expression studies, normalization may be performed using GmUBC4, GmUBC2, GmCYP2 and GmACT11 as reference genes. Our data indicate that both GmELF1A and GmTUA5 are the most stable reference genes for data normalization obtained from soybean roots infected with M. incognita, and GmCYP2 and GmELF1A are the most stable in soybean leaves infested with A. gemmatalis.ConclusionsFuture expression studies using nematode infection and caterpilar infestation in soybean plant may utilize the reference gene sets reported here.

Zantedeschia aethiopica is an evergreen perennial plant cultivated worldwide and commonly used for ornamental and medicinal purposes including the treatment of bacterial infections. However, the current understanding of molecular and physiological mechanisms in this plant is limited, in comparison to other non-model plants. In order to improve understanding of the biology of this botanical species, RNA-Seq technology was used for transcriptome assembly and characterization. Following Z. aethiopica spathe tissue RNA extraction, high-throughput RNA sequencing was performed with the aim of obtaining both abundant and rare transcript data. Functional profiling based on KEGG Orthology (KO) analysis highlighted contigs that were involved predominantly in genetic information (37%) and metabolism (34%) processes. Predicted proteins involved in the plant circadian system, hormone signal transduction, secondary metabolism and basal immunity are described here. In silico screening of the transcriptome data set for antimicrobial peptide (AMP) –encoding sequences was also carried out and three lipid transfer proteins (LTP) were identified as potential AMPs involved in plant defense. Spathe predicted protein maps were drawn, and suggested that major plant efforts are expended in guaranteeing the maintenance of cell homeostasis, characterized by high investment in carbohydrate, amino acid and energy metabolism as well as in genetic information.