Stringent response processes suppress DNA damage sensitivity caused by deficiency in full-length translation initiation factor 2 or PriA helicase.

When Escherichia coli grows in the presence of DNA-damaging agents such as methyl methanesulphonate (MMS), absence of the full-length form of Translation Initiation Factor 2 (IF2-1) or deficiency in helicase activity of replication restart protein PriA leads to a considerable loss of viability. MMS sensitivity of these mutants was contingent on the stringent response alarmone (p)ppGpp being at low levels. While zero levels (ppGpp°) greatly aggravated sensitivity, high levels promoted resistance. Moreover, M+ mutations, which suppress amino acid auxotrophy of ppGpp° strains and which have been found to map to RNA polymerase subunits, largely restored resistance to IF2-1- and PriA helicase-deficient mutants. The truncated forms IF2-2/3 played a key part in inducing especially severe negative effects in ppGpp° cells when restart function priB was knocked out, causing loss of viability and severe cell filamentation, indicative of SOS induction. Even a strain with the wild-type infB allele exhibited significant filamentation and MMS sensitivity in this background whereas mutations that prevent expression of IF2-2/3 essentially eliminated filamentation and largely restored MMS resistance. The results suggest different influences of IF2-1 and IF2-2/3 on the replication restart system depending on (p)ppGpp levels, each having the capacity to maximize survival under differing growth conditions.

Learning in Virtual Reality: Bridging the Motivation Gap by Adding Annotations.

One challenge while learning scientific concepts is to select relevant information and to integrate different representations of the learning content into one coherent mental model. Virtual reality learning environments (VRLEs) offer new possibilities to support learners and foster learning processes. Whether learning in VR is successful, however, depends to a large extent on the design of the VRLE and the learners themselves. Hence, adding supportive elements in VRLEs, such as annotations, might facilitate the learning process by guiding attention and supporting the selection of relevant information. Additionally, the mapping of pictorial and verbal information is eased by these annotations. The beneficial effect of annotations is highly dependent on learners' intrinsic motivation as intrinsic motivation while learning also affects the information selection and visual search patterns. In our experimental study (N = 61), we compared two conditions: learning in a VRLE with or without annotations. We measured the learning outcome on three different levels (knowledge, comprehension, and application). Additionally, we investigated intrinsic motivation as a moderator for the effect of annotations on learning outcome. We found no significant main effect of annotations on learning outcome. The moderating effect of intrinsic motivation for annotations on the overall learning outcome was significant. Our results imply that learners are either intrinsically motivated or need additional support by annotations as these support the selection of relevant information in the VRLE and therefore enable them to learn successfully. Which type or quantity of annotations supports learning processes best needs to be explored in future research.

Learning From Multiple Representations: Prior Knowledge Moderates the Beneficial Effects of Signals and Abstract Graphics.

Multimedia learning research addresses the question of how to design instructional material effectively. Signaling and adding graphics are typical instructional means that might support constructing a mental model, particularly when learning abstract content from multiple representations. Although signals can help to select relevant aspects of the learning content, additional graphics could help to visualize mentally the subject matter. Learners' prior knowledge is an important factor for the effectiveness of both types of support: signals and added graphics. Therefore, we conducted an experimental study situated in a university course of computer science with N = 124 participants. In our 2 × 2 factorial design, we investigated the effects of signals and illustrating graphics on learning outcomes and their potential interplay. Based on our regression analysis, we revealed prior knowledge as a significant moderator. Although learners with low levels of prior knowledge can profit from all types of help but still gain rather weak learning outcomes, learners with medium levels of prior knowledge profit from the synergy of both helps. With higher levels of prior knowledge, signals were particularly hampering. To improve the understanding of these supportive or hampering effects, a more fine-grained analysis of these processes and motivational effects is necessary.